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Falls risk in frail seniors : clinical and methodological studies Donaldson, Meghan Gordon 2007

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FALLS RISK IN FRAIL SENIORS: CLINICAL AND METHODOLOGICAL STUDIES by MEGHAN GORDON DONALDSON BHK, The University of British Columbia, 2000 M.Sc, The University of British Columbia, 2002 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in THE FACULTY OF GRADUATE STUDIES (Health Care and Epidemiology) THE UNIVERSITY OF BRITISH COLUMBIA JUNE 2007 © Meghan Gordon Donaldson, 2007 ABSTRACT INTRODUCTION: Falls in older adults are a significant cause of morbidity. Thirty percent of women and 25% of men aged 65 years and older fall at least once per year and 1 % of falls result in hip fracture. The effectiveness of current falls prevention guidelines has not been tested. One intervention to prevent falls is strength and balance retraining. AIMS: 1) to determine whether older women who present to the emergency department with a fall receive referrals consistent with published guidelines; 2) to determine whether a home-based strength and balance retraining program reduces fall risk as measured by a standardized physiological profile; 3) to undertake a review'of falls prevention literature to assess the appropriateness of statistical methods; 4) to explore the use of the mean cumulative function to compare fall events between groups. METHODS: 1) Telephone administered survey; 2) a randomized controlled trial (RCT) of the Otago Exercise Program versus standard care; 3) a systematic review of RCTs; 4) a simulation study of the mean cumulative function RESULTS: Thirty-two percent of women (95% confidence interval 21% to 43%) who fell reported a visit with their family physician and 24% (95% confidence interval, 14% to 34%) reported referral and care with a physiotherapist. The incidence rate ratio for falls for Exercise Program participants compared to standard care was 0.44 (95% CI 0.23-0.84). Among 84 published RCTs reviewed fewer than one third utilized statistical methods for recurrent events. The mean cumulative function is useful for graphically summarizing fall events over time. SUMMARY: Presentation to an emergency department after a fall is not currently associated with care consistent with published guidelines. Strength and balance retraining shows promise of reducing falls risk and further studies with larger samples are warranted. The analysis of falls could be improved by employing appropriate recurrent events models and informative graphical summaries. TABLE OF CONTENTS ABSTRACT ii TABLE OF CONTENTS iii LIST OF TABLES viii LIST OF FIGURES ix GLOSSARY OF TERMS AND ABBREVIATIONS x ACKNOWLEDGEMENTS xi CO-AUTHORSHIP STATEMENT xii 1 INTRODUCTION TO THE THESIS 1 1.1 References 3 2 LITERATURE REVIEW, RATIONALE, OBJECTIVES & HYPOTHESES 5 2.1 Introduction 5 2.2 Literature Review 5 2.2.1 Defining the scope of the thesis: Community-dwelling fallers 5 2.2.2 Incidence of falls 6 2.2.3 Economic burden of falls 7 2.2.4 Risk factors for falls in community-dwelling older adults 8 2.2.4.1 Clinical diagnoses associated with falls 8 2.2.4.2 Studies measuring physiological risk factors for falls 9 2.2.5 Physiological mechanisms that maintain postural stability to prevent falling 17 2.2.5.1 Age-related changes in the central nervous system 17 2.2.5.2 Age-related changes in the sensory system 17 2.2.5.3 Age-related changes in the musculoskeletal system 20 iii 2.2.6 Evidence for physical activity as a means of ameliorating risk factors for falls among community-dwelling older adults at increased risk for falls 21 2.2.7 Measurement of falls risk factors and falls 28 2.2.7.1 Measurement of falls risk factors 28 2.2.7.1.1 The Physiological Profile Assessment 28 2.2.7.1.2 Timed up and go test 40 2.2.7.1.3 Other physical performance tests 40 2.2.7.1.4 Force platform 41 2.2.7.1.5 Berg balance scale 42 2.2.7.2 The measurement and statistical analysis of falls 42 2.2.7.2.1 Measurement of falls 43 2.2.7.2.2 Statistical analysis of fall events 45 2.2.8 Falls Prevention Interventions 45 2.2.8.1 Vitamin D supplementation,psychotropic medication withdrawal, cardiac pacing, interventions to improve vision and home environment modification 46 2.2.8.2 Multifactorial interventions 47 2.2.8.3 Physical activity 48 2.2.8.3.1 The Otago Exercise Program 49 2.2.9 Clinical guidelines for falls prevention 55 2.2.10 Gaps in current knowledge that motivated my thesis studies 57 2.3 Rationale, Objective and Hypotheses 58 2.3.1 Study 1: Emergency department fall-related presentations do not trigger fall risk assessment: A gap in care of high-risk outpatient fallen? 58 2.3.2 Study 2: Action Seniors!: A randomised controlled trial of a home-based balance and strength retraining program 59 2.3.3 Study 3: A systematic review of statistical methods reported in randomized controlled trials of falls prevention in older adults 60 2.3.4 Study 4: The utility of the Mean Cumulative Function in detecting differences between groups experiencing different intensities of fall events 61 2.4 References 6 2 3 STUDY 1: EMERGENCY DEPARTMENT FALL-RELATED PRESENTATIONS DO NOT TRIGGER GUIDELINE ASSESSMENT: A GAP IN CARE OF HIGH-RISK OUTPATIENT FALLERS 71 3.1 Introduction 7 1 iv 3.2 Methods 72 3.3 Results 73 3.4 Discussion 73 3.5 References 78 4 STUDY 2: ACTION SENIORS!: A RANDOMIZED CONTROLLED TRIAL OF A HOME BASED BALANCE AND STRENGTH RETRAINING PROGRAM ON RISK FACTORS FOR FALLS IN OLDER MEN AND WOMEN WHO PRESENT TO A FALLS CLINIC AFTER SUSTAINING A FALL REQUIRING MEDICAL ATTENTION 79 4.1 Introduction 79 4.2 Methods 80 4.2.1 Randomisation—allocation concealment 81 4.2.2 Outcomes and covariates 81 4.2.2.1 Ascertainment of falls and adherence to the Otago Exercise Program 82 4.2.3 Sample Size 83 4.2.4 Intervention- Otago Exercise Program 83 4.2.5 Blinding 84 4.2.6 Statistical Analysis 84 4.2.6.1 Primary Analysis 84 4.2.6.2 Secondary Analysis 85 4.3 Results 85 4.3.1 Participant flow 85 4.3.2 Dropouts 85 4.3.3 Outcomes 86 4.3.4 Ancillary analyses 87 4.3.5 Adverse events 87 4.4 Discussion 87 4.4.1 Fall incidence reduction can exceed improvement in surrogate measures of fall risk profile 88 4.4.2 Role of adherence in effective exercise interventions 90 4.4.3 Clinical implications 90 4.4.4 Strengths, Limitations and Future Directions 91 4.5 References 1 ° 7 v 5 STUDY 3: A SYSTEMATIC REVIEW OF STATISTICAL METHODS REPORTED IN RANDOMIZED CONTROLLED TRIALS OF FALLS PREVENTION IN OLDER ADULTS 110 5.1 Introduction 110 5.2 Methods 112 5.3 Results 113 5.4 Discussion 114 5.5 References 120 5.6 References for all articles included in the systematic review (n=84) [1-84] 122 6 STUDY 4: UTILITY OF THE MEAN CUMULATIVE FUNCTION IN THE ANALYSIS OF FALL EVENTS 128 6.1 Introduction 128 6.2 Methods 129 6.2.1 Mean Cumulative Function 129 6.2.2 Simulation Studies 129 6.2.3 Analysis 130 6.3 Results 130 6.4 Discussion 131 6.5 References • 137 7 INTEGRATED DISCUSSION 139 7.1 Overview of findings 139 7.2 Impact and relevance for falls prevention initiatives in British Columbia 141 7.3 The challenge of delivering evidence-based physical activity to older adults 142 7.4 Future directions • 1^ 7.5 References 1 4 7 vi APPENDIX I: ETHICS 150 APPENDIX II: LETTER OF INITIAL CONTACT AND CONSENT FORM 153 APPENDIX III: DATA COLLECTION FORMS 163 APPENDIX IV: QUESTIONNAIRES 178 vii LIST OF TABLES Table 3-1 Injuries sustained by 226 women presenting to the ED with a fall 76 Table 4-1 Baseline demographic and clinical characteristics for the Otago Exercise Group and Standard of care Group 94 Table 4-2 Mean (± SD) Scores for the Physiologic Profile Assessment (PPA) and 'Timed up and Go' time at baseline and 6-months for Otago Exercise Group and Standard of care Group 97 Table 4-3 Regression table for unadjusted and adjusted values for PPA z-score, knee extension strength, sway on foam with eyes open and timed up and go (n=66). Adjusted estimates are adjusted for age, sex, referral route and falls clinic physician 98 Table 4-4 ANOVA table for unadjusted model (group and baseline score) and adjusted model (group, baseline score, age, sex, referral route, physician) for PPA z-score, knee extension strength, sway on foam with eyes open and "timed up and go" time 99 Table 4-5 Proportion (number) experiencing 0,1, 2, 3 and 4 or more falls during the follow-up period, incidence of fall events and follow up times in standard of care and OEP groups 101 Table 4-6 Recommendations to primary care provider at baseline and subsequent patient uptake at 6-months of published guidelines in the Otago Exercise Group and Standard of care Group 102 Table 5-1 Search strategy and number of papers retained at each stage 116 Table 5-2 Statistical methods with graphical display and number of papers (prevalence) by publication year 117 Table 5-3 Inferential statistics and number of papers (prevalence) by publication year 118 Table 5-4 Assumptions, strengths and limitations of three recurrent event statistical methods 119 Table 6-1 Average number of days to one fall event in groups A, B, C and D 134 Table 6-2 Distribution of subjects by the number of falls (percent), the average number of falls per subject and the number of prevented falls by intervention group 135 viii LIST OF FIGURES Figure 3-1 Eligible participants for telephone survey of fall follow-up care 75 Figure 4-1 CONSORT study flow diagram 93 Figure 4-2 The frequency of Physiological Profile Assessment z-score change from baseline to 6-months in the Otago Exercise Program group (group 1) and the standard of care group (group 0) 100 Figure 4-3 Mean Cumulative Function curves and 95% confidence intervals comparing the Otago Exercise Program group (+) and the standard of care group (*) 103 Figure 4-4 The Mean Cumulative Function difference curve and the 95% confidence interval comparing the Otago Exercise Program group and the standard of care group 104 Figure 4-5 Mean Cumulative Function curves and 95% confidence intervals comparing the Otago Exercise Program group (+) and the standard of care group (*) (n=3 outliers removed) 105 Figure 4-6 The Mean Cumulative Function difference curve and the 95% confidence interval comparing the Otago Exercise Program group and the standard of care group (n=3 outliers removed) 106 Figure 5-1 Assessment of studies for includsion in RCTs of recurrent events 115 Figure 6-1 The Mean Cumulative Function (left) and the Mean Cumulative Function difference (right). Legend: I Group A compared to Group B; II Group A compared to Group C; III Group A compared to Group D 136 ix GLOSSARY OF TERMS AND ABBREVIATIONS ABBREVIATION DEFINITION _ Control CI Confidence interval CONSORT Consolidated Standards of Reporting Trials DXA Dual energy x-ray absoptiometry ECS Edge contrast sensitivity, as measured by the Melbourne Edge Test HS Home safety I Intervention IRR Incidence rate ratio KES Knee extension strength, as measured by strain gauge dynamometer MCF Mean cumulative function NR Not reported OEP Otago Exercise Program OR Odds ratio OT Occupational therapist PPA Physiological Profile Assessment PT Physiotherapist QUOROM .Quality Of Reporting Of Meta-analyses RCT Randomized controlled trial RR Relative risk SV Social visits TUG Timed up and go ACKNOWLEDGEMENTS I am indebted to my two thesis supervisors—Drs. Karim Khan and Patti Janssen. Karim, I cannot imagine completing this thesis without your friendship, encouragement and mentorship. You always give so much of yourself to all of your students, and I just want to thank you for that. Patti, thank you for taking a chance on me. You willingly forayed into a topic area that was not familiar to you. You have challenged me to think critically over the years, right from day one in HCEP 502! Patti, I particularly want to thank you for taking the time out of your busy schedule in the last few weeks to provide 'hands-on' feed-back. I certainly learned a lot. To my committee members—Drs. Boris Sobolev, Wendy Cook, Heather McKay. Boris, thank you for making yourself available throughout the course of my thesis-1 always felt like your door was open. I will remember that Saturday in February 2007 that I spent at the white-board on the 7 t h floor for many years to come. Wendy, as you know I will be forever grateful to you for all of your energy in the clinic—I cannot imagine doing that without you. I also want to thank you for always providing timely and insightful feedback on this thesis. I have to say that it is too bad we are the same age—I was hoping you'd look after me when I get older! Heather—I will be eternally grateful that you took a chance in September of 2000. Thank you for the mentorship, friendship and encouragement over the years (I won't say how long!). A huge 'thank you' to all of the participants in this study. I could not have completed this thesis without your volunteerism and dedication to the study. You've all made this work seem all the more meaningful. Thank you to Margie Bell for providing the very best support in all ways—I could not have done this without you. Big thanks to Ria Hechanova for your incredible patience and organizational skills—the clinic and the study would not have run so smoothly if it wasn't for you. And, to Ann Donaldson for being a very trustworthy and reliable research assistant. I know the participants enjoyed the study as much as they did because of your monthly phone calls to "check-in". Lisa Kuramoto—thank you for introducing me to the wonderful world of SAS and for patiently answering my questions. To the Bone Health Research Group—I have enjoyed all of the years of stimulating Journal Club, and looking forward to more of them in the future. A big thank you to Dr. Penny Brasher—I am so glad that you have been a part of the BHRG and that you have willingly entertained all of my questions on so many occasions. I'd particularly like to thank Drs. Heather Macdonald, Saija Finland (aka Kontulainen), Maureen Ashe, Teresa Ambrose and (soon to be) Emily McWalter. I absolutely could not have made it through the last four and a half years without you (the last five months particularly). To my great friends Nicky Pieckenhagen and Sylvia Struck. Thank you to both of you for always being a phone call or email away. To my family—Mom, Dad, Melissa, Timothy and Marc (like it or not, you are part of the clan now!)—thank you for supporting me through thick and thin, I could not have done this without all of you. And to Marc—looking forward to the next chapter. xi CO-AUTHORSHIP STATEMENT Sections of this thesis have been published as multi-authored manuscripts in peer-reviewed journals and are indicated with * beside the publication below. Details of the authors' contributions are provided where relevant. We agree with the stated contributions of the thesis author as indicated below. Dr. Karim Miran-Khan (Thesis Co-Supervisor) Dr. Patricia Janssen (Thesis Co-Supervisor) Publications 1. Donaldson MG*, Khan KM, Davis JC, Salter AE, Buchanan J, McKnight D, Janssen PA, Bell M, McKay HA. Emergency Department fall-related presentations do not trigger fall risk assessment: a gap in care of high risk out-patient fallens. Arch Gerontol Geriatr. 2005 Nov-Dec;41(3):311-7. Authors' contributions: Meghan Donaldson was responsible for the original ideas behind the manuscript, analysis and writing the original publication. Karim Khan guided all aspects of the research. Karim Khan and Patricia Janssen were the key editors of this manuscript. Karim Khan, Patricia Janssen, Jennifer Davis, Alison Salter, Jan Buchanan, Doug McKnight, Margie Bell and Heather McKay participated in the design of the study, stimulated discussion of the results and provided editorial assistance. 2. Donaldson MG*, Sobolev B, Kuramoto L, Cook WL, Khan KM, Janssen PA. Utility of the Mean Cumulative Function in the analysis of fall events. J Gerontol A Biol Sci Med Sci. 2007 Apr;62(4):415-9. Authors' contributions: Meghan Donaldson was responsible for the original ideas behind the manuscript, analysis and writing the original publication. Boris Sobolev guided all aspects of the research. Boris Sobolev, Karim Khan and Patricia Janssen were the key editors of this manuscript. Lisa Kuramoto performed the simulations. Boris Sobolev, Karim Khan, Patricia Janssen, Lisa Kuramoto and Wendy Cook participated in the design of the study, stimulated discussion of the results and provided editorial assistance. 3. Donaldson MG*, Sobolev B. Are all falls equal? BMJ on-line 13 May 2004 [letter], http://bmi.bmiiournals.com/cai/eletters/328/7441/676 xii Authors' contributions: Meghan Donaldson was responsible for the original ideas behind the letter and writing the original letter. Boris Sobolev guided all aspects of the letter and was the key editor of this manuscript. Manuscript Submitted 1. Donaldson MG, Sobolev B, Khan KM, Cook WL, Janssen PA. A systematic review of statistical methods reported in randomised controlled trials of falls prevention. (BMJ, submitted February 28 t h, 2007) Authors' contributions: Meghan Donaldson was responsible for the original ideas behind the manuscript, analysis and writing the original publication. Boris Sobolev guided all aspects of the research. Boris Sobolev, Karim Khan and Patricia Janssen were the key editors of this manuscript. Boris Sobolev, Karim Khan, Wendy Cook and Patricia Janssen participated in design of the study, stimulated discussion and provided editorial assistance. Manuscript in Progress 1. Donaldson MG, Khan KM, Cook WL, Sobolev B, McKay HA, Janssen PA.. Action Seniors!: An RCT of the Otago home-based exercise program. Authors' contributions: Meghan Donaldson was responsible for the original ideas behind the manuscript, analysis and writing the manuscript. Karim Khan and Patricia Janssen guided all aspects of the research and are the key editors of this manuscript. Wendy Cook was involved in planning the trial. Boris Sobolev guided the statistical analysis of this manuscript. Karim Khan, Wendy Cook, Boris Sobolev, Heather McKay and Patricia Janssen participated in the design of the study, continue to stimulate discussion and are providing editorial assistance. Abstracts 1. Donaldson MG, Salter AE, Khan KM, Buchanan J , McKnight D, Brubacher J , Janssen PA, McKay HA. Patient management after emergency department fall-related injury: Exercise prescription is 'standard of care' but does it occur? Med Sci Sports Exerc 2003; 2. Donaldson MG, Khan KM, Sobolev B, Kuramoto L, Cook WC, Janssen P, McKay HA. The Utility of the Mean Cumulative Function in the Analysis of Recurrent Falls. XXI Paulo Symposium on Bone Fragility and Fractures. Tampere, Finland. May 7-9, 2006. 3. Donaldson MG, Khan KM, Cook WL, Sobolev B, McKay HA, Janssen PA. Action Seniors!: An RCT of the Otago home-based exercise program. ASBMR Annual General Meeting 2007. xiv 1 Introduction to the Thesis Falls are a significant cause of morbidity and mortality in older adults [1], Approximately 30% of adults over the age of 65 experience at least one fall each year and half experience two or more falls each year [2-4]. Over 90% of hip fracture are caused by a fall [5,6] and of community-dwelling seniors who fracture their hip, 20% will die and 15% will be transferred to long term care within 12 months of the event [7],The mean one-year cost associated with falls in Canada is estimated to be $980 million [8].The mean one-year cost of hip fractures in Canada is estimated to be $650 million [7] and is expected to increase to $2.4 billion by 2041 [7]. The contribution of falls to hip fracture has been overlooked in the literature [9], While low bone mass is assumed to be the key risk factor for hip fracture, [10,11] half of all hip fractures occur in the absence of osteoporosis [12]. Other risk factors for falls include impaired vision [4,13], use of psychotropic medication [2,3,14], carotid sinus syndrome [15-17], cognitive impairment [2,18], and deficits in lower extremity strength and balance [2-4,19]. Older people often have more than one risk factor for falls [2, 3] and lower extremity strength and balance deficits are the most prevalent. Interventions such as withdrawal from psychotropic medications [20] and insertion of pacemakers [15] have been effective interventions to prevent falls, however, these interventions do not wholly address underlying weakness in the lower extremities or poor balance. Conversely, physical activity interventions have been successful in improving strength and balance, and preventing falls [21-24].Therefore, this dissertation investigates the role of physical activity, specifically strength and balance training, in ameliorating risk factors for falls and preventing falls in the elderly. A comprehensive literature review was undertaken to identify risk factors for falls, methodology issues in the measurement of falls, and the role of physical activity as an intervention strategy to prevent falls. This synthesis of evidence is presented in Chapter 2. Specifically, I outline the epidemiology of falls and hip fractures, age-related changes in physiology that contribute to falls risk, screening tools used to identify at-risk individuals, the evidence for effectiveness of falls prevention interventions, and gaps in knowledge translation related to falls prevention. I conclude Chapter 2 with the rationale, objectives and hypotheses for the four studies that constitute my thesis. My initial study, outlined in Chapter 3, surveyed women who had been treated for a fall-related injury at the Vancouver Hospital emergency department to evaluate whether their care was consistent with published guidelines. The finding that their care did not include appropriate referrals prompted a follow-up prospective study by Salter and colleagues to which I contributed, but which is not part of my PhD thesis [25]. In that study, 90% of older men and women who attended the emergency department for a fall-related injury did not receive appropriate referrals and their falls risk profile worsened significantly over a 6-month period following their fall. 1 This clear absence of appropriate follow-up justified the conception of a randomized controlled trial (RCT) of a home-based strength and balance retraining program versus standard care to ameliorate risk factors for falls (Chapter 4). Risk factors for falls were measured by a standardized physiological profile among seniors who had previously fallen and who accessed the single falls clinic in Vancouver, British Columbia. Falls are not independent events, as the risk of sustaining a subsequent fall increases after the first event. To understand how recurrent events have been analyzed in the falls literature, I conducted a systematic review of RCTs of falls prevention interventions (Chapter 5). I concluded that RCTs reporting recurrent events could be improved by using recurrent event models and informative graphical displays. To further address the analysis of recurrent events, I explored the use of the mean cumulative function (MCF) to compare the occurrence of falls between groups (Chapter 6). The MCF is a summation method first utilized in the reliability literature. It estimates the mean number of fall events per person within a specified time as opposed to methods in current use which measure time to first fall per person. Finally, in Chapter 7,1 provide an integrated discussion of the four studies and suggest directions for future methodological and clinical research. 2 1.1 References 1. Tinetti, M.E. and C.S. Williams, Falls, injuries due to falls, and the risk of admission to a nursing home. N Engl J Med, 1997. 337(18): p. 1279-84. 2. Tinetti, M.E, M. Speechley, and S.F. Ginter, Risk factors for falls among elderly persons living in the community. N Engl J Med, 1988. 319(26): p. 1701-7. 3. Campbell, J , M. Borrie, and G. Spears, Risk factors for falls in a community-based prospective study of people 70 years and older. J Gerontol A Biol Sci Med Sci, 1989.44(4): p. M112-M117. 4. Lord, S.R, et al . Physiological factors associated with falls in older community-dwelling women. JAGS, 1994. 42: p. 1110-1117. 5. Nguyen, N.D, et al. Identification of high-risk individuals for hip fracture: a 14-year prospective study. J Bone Miner Res, 2005. 20(11): p. 1921-8. 6. Parkkari, J , et al . Majority of hip fractures occur as a result of a fall and impact on the greater trochanter of the femur: a prospective controlled hip fracture study with 206 consecutive patients. Calcif Tissue Int, 1999. 65(3): p. 183-7. 7. Wiktorowicz, M, et al . Economic implications of hip fracture: Health services use, institutional care and cost in Canada. Osteoporosis International, 2001.12(4): p. 271-8. 8. SmartRisk, Economic burden of unintentional injury in British Columbia. 2001, British Columbia Injury Research and Prevention Unit: Vancouver, p. 36. 9. Robinovitch, S.N, et al . Strategies for avoiding hip impact during sideways falls. J Bone Miner Res, 2003. 18(7): p. 1267-73. 10. Cummings, S , et al . Risk factors for hip fracture in white women: The Study of Osteoporotic Fractures reserach group. New England Journal of Medicine, 1995. 332(12): p. 767-73. 11. Dargent-Molina, P, et a l . Fall-related factors and risk of hip fracture: the EPIDOS prospective study. Lancet, 1996. 348(9021): p. 145-9. 12. Wainwright, S.A, et al. Hip fracture in women without osteoporosis. J Clin Endocrinol Metab, 2005.90(5): p. 2787-93. 13. Lord, S.R, Visual risk factors forfaits in older people. Age Ageing, 2006. 35 Suppl 2: p. ii42-ii45. 14. Leipzig, R.M, R.G. Cumming, and M.E. Tinetti, Drugs and falls in older people: a systematic review and meta-analysis: I. Psychotropic drugs. J Am Geriatr Soc, 1999.47(1): p. 30-9. 15. Kenny, R.A, et al . Carotid sinus syndrome: a modifiable risk factor for nonaccidental falls in older adults (SAFE PACE). J Am Coll Cardiol, 2001. 38(5): p. 1491-6. 16. Davies, A. and R. Kenny, Falls presenting to the accident and emergency department: Types of presentation and risk factor profile. Age and Ageing, 1996.25: p. 362-366. 3 17. Davies, A.J., N. Steen, and R.A. Kenny, Carotid sinus hypersensitivity is common in older patients presenting to an accident and emergency department with unexplained falls. Age Ageing, 2001. 30(4): p. 289-93. 18. Close, J.C, et al., Predictors of falls in a high risk population: results from the prevention of falls in the elderly trial (PROFET). Emerg Med J, 2003.20(5): p. 421-5. 19. Nevitt, M.C., etal., Risk factors for recurrent nonsyncopal falls. A prospective study. Jama, 1989.261(18): p. 2663-8. 20. Campbell, A.J., et al., Psychotropic medicine withdrawl and a home-based exercise program to prevent falls: a randomized controlled trial. J Am Geriatr Soc, 1999. 47: p. 850-853. 21. Carter, N., et al., Community based exercise program reduces fall risk factors in 65-75 year old women with osteoporosis: a randomized controlled trial. Canadian Medical Association Journal, 2002.167(9): p. 997-1004. 22. Lord, S.R. and S. Castell, Physical activity program for older persons: effect on balance, strength, neuromuscular control and reaction time. Arch Phys Med Rehavil, 1994.75: p. 648-652. 23. Campbell, A.J., et al., Randomized controlled trial of a general practice programme of home based exercise to prevent falls in elderly women. BMJ, 1997. 315: p. 1065-1069. 24. Liu-Ambrose, T., et al., Resistance and agility training reduce fall risk in women aged 75 to 85 with low bone mass: a 6-month randomized, controlled trial. J Am Geriatr Soc, 2004.52(5): p. 657-65. 25. Salter, A.E., et al., Community-dwelling seniors who present to the emergency department with a fall do not receive Guideline care and their fall risk profile worsens significantly: a 6-month prospective study. Osteoporos Int, 2006.17(5): p. 672-83. 4 2 Literature Review, Rationale, Objectives & Hypotheses 2.1 Introduction This literature review has 9 principal sections. In relation to falls, I discuss the relevance of the setting where fallers reside, incidence and health care costs, and key risk factors. To set the scene for the research methods used in my thesis, I review ways of measuring falls risk factors and ways of defining, enumerating, and analysing falls. I then review fall-prevention interventions, clinical guidelines and gaps in current knowledge. The final section of the chapter outlines the rationale, objectives and hypotheses for the four studies that constitute this thesis. 2.2 Literature Review 2.2.1 Defining the scope of the thesis: Community-dwelling fallers In falls research, it is usual to distinguish between community-dwelling and institutionalized persons (e.g., residing in nursing home, long term care) for several reasons. Intervention strategies that reduced falls in the community-dwelling population [1-4], for example strength and balance retraining, have not always been effective in the institutional setting [5,6]. Kerse and colleagues conducted a cluster randomized controlled trial of a multifactorial intervention to prevent falls in residential care facilities in New Zealand [6], The intervention was associated with an increased risk for falls compared to usual care (incident rate ratio=1.34, 95% confidence intervah .06 to1.72). The authors postulated that the intervention increased the rate of falls because the intervention group, who participated in strength and balance training, were exposed to more opportunities to fall. In Canada, mild cognitive impairment and frank dementia are more prevalent among those living in institutional settings than those living in the community [7]. The Cochrane review of falls prevention interventions concluded that there was insufficient evidence from randomized controlled trials to support interventions in populations with cognitive impairment [8].A more recent meta-analysis that included 43 randomized controlled trials of interventions to prevent falls supports this conclusion [9]. In the population of seniors, residing in long term care is a characteristic that identifies populations with a higher prevalence of cognitive impairment [7]. The remainder of this literature review, and my studies in Chapters 3 and 4, relate to community-dwelling fallers who are considered to be cognitively intact. 5 2.2.2 Incidence of falls To my knowledge, only one prospective study of community-dwelling older adults in Canada assessed the incidence of falls in 1993.0'Loughlin and colleagues enrolled 409 community-dwelling men and women aged 65 years and older and prospectively monitored falls for 48 weeks [10]. The participants were telephoned every 4 weeks to ascertain the number of falls since the previous telephone call. The authors reported 29% of this population fell at least once, and 11.5% fell two or more times. The falls rate in this population of Quebec-Canadians was 0.5 falls per person-year [10]. Several prospective cohort studies have documented the incidence of falls in community-dwelling older adults in the United States [11], New Zealand [12] and Australia [13] (Table 2.1). In 1988Tinetti and colleagues enrolled 336 American men and women aged 75 years and older and monitored them prospectively for one year. Falls were ascertained with a falls diary completed by the participant each month and participants were telephoned every other month by study personnel. The authors reported that 32% of this population fell at least once, and 9% fell two or more times. The falls rate in this population was 0.8 falls per person-year. The following year, Campbell and colleagues published a one-year prospective cohort study that included 761 New Zealand men and women aged 70 years and older [12]. Falls were ascertained with both monthly falls diary and monthly telephone calls by research nurses. To augment the reporting of falls, participants and the relatives of those participants with known memory impairment were contacted monthly by telephone. This study reported that 39% of women and 28% of men fell at least once. The falls rate was 0.6 falls per woman-year and 0.5 falls per man-year. This was the first study to report proportion and rate of falls separately for men and women and suggested that women may be at increased risk of falls compared with men. In 1994, Lord and colleagues enrolled 341 Australian women aged 65 years and older [13]. Falls were ascertained with a falls diary that participants returned by mail each month. In this study, 39% of women fell at least once and 21% fell at least twice. Although the falls rate was not reported, I estimated this to be 0.8 falls per woman-year (I assumed that all women contributed a full year of follow-up). Overall, these four studies suggest that 28 to 39% of older adults aged 65 years and older fall at least once each year, and that between 9 and 21% fall at least twice each year. One study from New Zealand suggested that a greater proportion of women (30%) fall each year as compared with men (25%) [12]. Overall, the rate of falls in these populations, I selected based on age alone, ranged from 0.5 falls per person-year [10] to 0.8 falls per person-year [11,13]. I compare those rates with similarly-aged community-dwelling persons who might be considered at 'higher risk' by definition of having had at least one fall in the previous year (please see Table 2.2). I highlight three prospective cohort studies that were conducted in the United States, the UK and Finland that enrolled participants who had a history of at least one fall in the previous year [14-16]. In 1989, Nevitt and colleagues published a prospective cohort study that enrolled 325 men and women aged 60 years and older [14]. Falls were ascertained by a weekly telephone call. A nurse examined each participant after they fell and documented the circumstances of the event. In this 6 population of older Americans, 57% fell at least once and 31 % fell at least twice. The falls rate in this population was 1.6 falls per person-year. In 2003, Close and colleagues reported results specific to the control group enrolled in their randomized controlled trial, Prevention of Falls in the Elderly Trial (PROFET) [15]. Participants in this UK study were aged 65 years and older and had attended the emergency department due to a fall. Falls were ascertained for one year by postal questionnaire at 4,8 and 12 months. In this population of older men and women with a previous fall, 52% fell at least once and 26% fell three or more times. The falls rate was 2.4 falls per person-year. Finally, in 2006, Lehtola and colleagues enrolled 555 Finnish men and women aged 85 years and older [16]. Falls were ascertained by bimonthly telephone calls from the research staff for two years. In this population, 74% of participants fell at least once and 47% fell at least twice during the two-year follow-up period. The rate of falls was 1 fall per woman-year and 0.8 falls per man-year. In these cohorts, the proportion of participants who fell ranged from 52% [2,15] to 58% [14]. The rate of falls ranged from 1 fall per person year [16] to 2.4 falls per person year [2,15]. When participants for cohort studies are selected based on a history of at least one fall in the previous year, both the proportion of persons experiencing a fall and the rate of falls increases compared to older persons selected on the basis of age alone. Expressed crudely, the proportion of fallers in these cohort studies is approximately twice that of persons enrolled in cohort studies based on age alone; the rate of falls is 2-3 times that of the 'unselected' community-dwelling population. 2.2.3 Economic burden of falls In Canada, the direct health care costs of falls was published in a 1998 study using data from the Canadian Institute for Health Information data from 1994 [17]. Falls were responsible for 71% of hospitalizations due to unintentional injury in those 61-70 years of age; the proportion was 88% among those 71 years of age and older. The direct cost of falls was $2.4 billion, which represents 55% of the total cost to treat unintentional injuries in Canada. The direct cost of falls in those 60 years and older is approximately $980 million. The estimated total cost for treating falls in Canada, including direct and indirect costs, was $3.6 billion; this figure is approximately twice the cost of treating motor vehicle accidents. In British Columbia, the estimated direct cost for treating falls in persons aged 65 years and older was $180 million, and this represented approximately 9% of the total cost for treating all injuries in the province [18]. A recent study conducted in the United States estimated that the direct medical cost per fall was $2,591 in 2002 dollars [19]. Another recent study from the United States aimed to report the cost per fall based on three different scenarios. Costs for hospital admission, emergency department visit, or falls requiring office/outpatient visits cost $22,260, $3890 and $5040 respectively over a one-year follow-up period [20]. 7 2.2.4 Risk factors for falls in community-dwelling older adults Risk factors for falls can be grouped in several ways. One approach is to consider the risk factor as either medical factors including comorbidities and medication [21-23] or as physiological factors (e.g., strength, balance).This approach contrasts the "medical model" with a "physiological model". As the focus of this dissertation is on physiological risk factors, I only briefly present an overview of medical factors relating to risk factors for falls (please see Tables 2.1 and 2.2 for study details). 2.2.4.1 Clinical diagnoses associated with falls Although more prevalent among those living in long-term care facilities, impaired cognition is a well-established risk factor for falls that is also prevalent among community-dwelling older adults [2,11,15,23]. However, the extent to which cognitive impairment increases fall risk is not completely understood in the community-dwelling population because cohort studies generally identify and exclude persons who do not score above a certain threshold on screening tools for cognitive impairment (e.g., Mini Mental State Exam [24] and Abbreviated Mental Test [25], Cognitive impairment may affect falls risk by influencing complex motor movements and their organization (e.g., remembering how to use a walker safely), visuospatial deficits (e.g., getting lost, judging distances) and executive function (complex planning and organization) [26], A more sensitive measure of cognitive impairment than the screening tools discussed above is achieved with neuropsychological testing [27]. People can score above 24 points on the Mini Mental State Exam (a score below which, cognitive impairment is assumed) but can demonstrate substantial deficits on the more sophisticated cognitive tests (e.g., Montreal Cognitive Assessment [28]). In a recent validation study, Nasreddine and colleagues demonstrated that in persons with mild cognitive impairment (MCI) (defined as an intermediate clinical state between normal cognitive aging and dementia) criteria supported by psychometric measures, the Mini Mental State Exam (MMSE) had a sensitivity of 18% whereas the Montreal Cognitive Assessment (MoCA) detected 90% of the MCI participants. Both the MMSE and MoCA reported specificities of 100% and 87% respectively [28].This raises the possibility that persons deemed to be "without cognitive impairment" by the Mini Mental State Exam may in fact demonstrate some degree of impairment by neuropsychological testing. This may influence interventions for falls prevention because cognitive impairment may affect adherence to intervention recommendations. A number of comorbid medical conditions have been identified as risk factors for falls. They include knee osteoarthritis [12,14], stroke [12], chronic kidney disease [29, 30], foot and gait morbidity [11,31] dizziness [10],morbidity associated with vision (e.g., age-related macular degeneration, cataracts and glaucoma) [32,33] and Parkinson's disease [14,34]). As will be discussed in section 1.2.4.2, the association between comorbid conditions and the risk of falls may manifest through impairments in physiological domains of balance, strength, reaction time, proprioception and vision. 8 Medications, such as psychotropic agents [12, 35, 36] and sedatives in particular [11, 35,36] have been implicated in increased falls risk. In addition, the total number of medications a person is currently prescribed is also a recognised risk factor for falls [2,11,12,15,37]. The number of medications prescribed is likely to be associated with the number of comorbid conditions. Studies of older adults should document current medication usage and medical comorbidities. The association between medications and falls is likely mediated by the side effects of the medications such as reduced mental alertness, slowed transmission within the central nervous system, sedation, blurred vision, confusion, neuromuscular incoordination, impaired balance [36,38,39]. Additional elements that can be elucidated in a medical history are risk factors for falls. As discussed in section 2.2.2 a strong predictor of falls is a history of at least one fall in the previous year (RR 3.0) [2,10-12,14,15,23]. Indoor falls, compared with outdoor falls, are associated (RR 2.4) with an increased risk of future falls [15,40]. There is a strong association between risk of falls and age [12,23]; being aged 80 years and older confers a relative risk of 1.7 compared with those less than 80 years [11,12]. Persons who attend the emergency department due to a fall-related injury [2, 3] represent a population that may be particularly suitable for intervention as they are at risk of future falls. Furthermore, they have presented themselves to a health service, and thus, 'case-finding' is simplified. My thesis will focus on community-dwelling persons with a history of falling in the previous year. 2.2.4.2 Studies measuring physiological risk factors for falls Although attributing risk for falls to specific medical diagnoses might have a clinical purpose, it is not ideal in the research setting because the severity of these conditions may vary among persons. Further, persons who demonstrate age-associated changes in sensorimotor function and inactivity may present with these impairment but without underlying documented illness [41].Thus, a "physiological approach" deals with impairments irrespective of their cause [41]. Cohort studies that enrolled community-dwelling older adults in Canada and in other countries and have reported the incidence of falls were discussed in section 2.2.2 [10-16,42]. Several of these studies also measured physiological risk factors for falls and their association with the incidence of falls. In this section I detail these cohort studies and in the following section I describe the age-associated changes in these physiological systems that are associated with increased risk for falls. As described in section 2.2.2,0'Loughlin and colleagues conducted the only Canadian prospective cohort study that examined the relationship between risk factors for falls and the incidence of falls [10]. Physiological factors were not assessed directly but were ascertained by an interviewer-administered structured questionnaire. In this study of 409 9 Quebec-Canadians aged 65 years and older reporting difficulty to walk 400 metres was positively associated with increased risk for falls (IRR 1.6, 95% C11.2 to 2.4). Outside of Canada, the first prospective cohort study designed to ascertain risk factors for falls in community-dwelling older adults was published in 1988 by Tinetti and colleagues [11]. In this study, 336 persons aged 75 years and older were enrolled in Connecticut and followed prospectively for one year. Physiological risk factors measured at baseline and positively associated with the incidence of falls were lower-extremity disability, foot morbidity and balance and gait abnormalities. This study demonstrated a dose-response relationship between the number of gait and balance abnormalities and the risk of falls (see Table 2.1). The following year, Campbell and colleagues reported on 761 New Zealanders aged 70 years and older [12]. Participants in this study were monitored for one year. Baseline grip strength and sway were positively associated with the incidence of falls. The same year, Nevitt and colleagues reported that impaired balance (as measured by tandem gait) was associated with an increased risk for falls in 325 Americans aged 60 years and older with a history of at least one fall [14]. Ten years later, Davis and colleagues reported on 705 Japanese women in Hawaii. Poor balance (defined as the inability to hold a tandem stance for 10 seconds), impaired quadriceps strength (lowest quartile versus highest quartile) and increased time to complete five chair stands (fastest quartile versus slowest quartile) were positively associated with increased risk for falls [42]. Lord and colleagues approached falls risk factor assessment differently. They argued that from a physiological perspective, the association between diseases, medications and age, and increased falls risk would manifest through impairments in the five domains of strength, balance, position sense, reaction time, and vision [13,41,43]. Lord and colleagues developed a series of tests to measure risk factors in the five domains. These tests are now known as the Physiological Profile Assessment, and this is discussed in detail in section 2.2.7.1.1. These Australian researchers enrolled 373 community-dwelling Australians aged 65 years and older and monitored them for one year [13]. Baseline values of vision (edge contrast sensitivity, visual acuity), position sense (lower limb proprioception, vibration sense at the tibial tuberosity), strength (quadriceps, ankle dorsiflexor), reaction time and sway (eyes open and close on firm and compliant surfaces) were all positively associated with risk of falls. A discriminant function analysis demonstrated that five tests (edge contrast sensitivity, proprioception, quadriceps strength, hand reaction time, sway eyes open on compliant surface), could distinguish persons with multiple falls (two or more) from persons with zero or 1 fall. Consistent with Lord's approach, a number of physiological factors have been identified as risk factors for falls in community-dwelling older adults. Factors that arise consistently include impaired balance [11-14], lower limb weakness [11-14], slow gait speed [10], poor edge contrast sensitivity [13], impaired ankle strength [13], slow hand reaction time [13], impaired vision [13,32,33]. These risk factors are captured using the Physiological Profile Assessment tool, and this will be discussed in detail in section 2.2.7.1.1 [41]. Of particular importance are 10 neurological functions including balance and muscle strength, the following section describes the age-associated changes that occur in balance and strength. 11 Table 2-1 Cohort studies of falls and fall risk factors among community-dwelling older adults by year of publication Population USA; men (n=151)and women (n=185); ^ 75 yrs; 1 year follow-up Author, year Ascertainment of fall/fractures Risk Factors (RF) identified Incidence of falls Tinetti and colleagues. 1988 [11] Telephone interview with subject every other month Telephone interview with proxy at study end and when nurse-researcher doubted the subject's reliability Falls diary left with subject (instructions given to a proxy as well) RFfor>1fall: RF Adj OR (95% CI) Sedatives 28.3 (3.4-239.4) Cognitive impairment 5.0(1.8-13.7) Lower-extremity disability 3.8 (2.2-6.7) Palmomental reflex 3.0(1.5-6.1) Foot problems 1.8(1.0-3.1) No of gait and balance abnormalities 0-2 1.0 3-5 1.4 (0.7-2.8) 6-7 1.9(1.0-3.7) roportion of subjects having > 1 fall increases with the number of RFs present 272 falls 32% 1+fall 0.8 falls per person-yr Of those who fell: 46% 1 fall 29% 2 falls 25% 3+ falls Injurious falls: 26 (8.6%) subjects serious injury 29 (11.6%)serious injuries 20 (7%)fractures 4 (1.5%)hip fractures Author, year Population Ascertainment of fall/fractures Risk Factors (RF) identified Incidence of falls Campbell and colleagues. 1989[12] New Zealand men and women; n=761;>70 years; 1 year follow-up Falls diary with monthly phone call by research nurses Relatives of those with memory impairment were contacted monthly Matrons in residential facilities recorded falls RF for > 1 fall women: RF Adjusted OR (95% CI) 75-79 yrs (v 70-74 yrs) 1.2(0.7-2.2) 80-84 yrs 2.5(1.3-5.0) 85-59 yrs 2.5(1.0-6.2) 90+ yrs 8.1 (1.2-56.1) Freq. outdoors 2.0 (0.8-4.8) Drugs 1-3 (vO drugs) 2.6(1.2-5.5) Drugs 4+ 4.5(1.9-10.6) Psychotropics 1.6(1.0-2.8) Knee OA 1.8(1.1-2.8) Stroke 13.6 (2.6-71.3) Body sway 1.7(1.0-2.9) Grip strength 1.7 (0.9-3.1) 39% women 1 +falls 28% men 1+falls 0.6 falls per woman yr 0.53 falls per man yr RFfor> 1 fall men: RF Adjusted OR (95% CI) 75-79 yrs 2.2(1.0-4.7) 80-84 yrs 1.6 (0.6-3.9) 85-89 yrs 2.9 (0.8-11.0) 90+ yrs 1.2(0.1-13.6) Unable to rise from chair 3.4(1.4-8.4) stroke 1.8(0.6-5.8) Knee OA 2.7 ()1.3-5.3 Body sway 2.6(1.3-5.1) O'Loughlin and colleagues. 1993 [10] Canada; n=409; men and women; > 65 years; 48 wks follow-up Telephone call every 4 weeks Dizziness incidence rate ratio (IRR)=2 Frequent physical activity IRR=2 Slow time to walk 400m IRR=1.6 Protective factors: diversity of Physical activities IRR=0.6; daily alcohol consumption (IRR=0.5); days in bed due to poor health (IRR=0.5); heart medication (1RR=0.6); hx of falls (IRR=2.6) 29% fell (17.6% fell once; 11.5% fell 2+ times) 0.5 falls per person-yr Author, year Population Ascertainment of fall/fractures Risk Factors (RF) identified Incidence of falls Lord 1994 [13] Australia; n=373; > 65 years; 12 month follow-up Falls diary ECS, visual acuity, proprioception, vibration sense, quadriceps strength, ankle strength, reaction time and all measures of sway (eyes open/closed on firm/compliant surfaces) Discriminant Function (between multiple and non-multiple fallens): ECS, proprioception, quadriceps strength, reaction time, sway eyes open on compliance surface 39% 1 -»- fall -0.8 falls per person-year Table 2-2 Cohort and cross-sectional studies of falls and fall risk factors among community-dwelling older adults who had fallen prior to study entry, by year of publication Author, year Population Ascertainment of fall/fractures Characteristic/Risk Factors identified Incidence of falls Nevitt and colleagues. 1989 [14] USA; (n=59) and women (n=266): >60 yrs; s 1 fall in previous year; 1 year followup; mean age = 70.3 yrs Weekly ascertainment Nurse examination post fall RF for > 2 falls: -1.6 falls/person-yr 490 falls 57% at least 1 fall 25% only 1 fall 31% 2+falls 19% 3+falls RF Adjusted OR (95% CI) White 2.4(1.1-5.3) > 3 fall in previous year 2.4(1.3-4.4) previous fall with injury 3.1 (1.5-6.4) arthritis 2.7(1.3-5.6) Parkinson's disease 9.5(1.8-50.1) difficulty standing up from a chair 3.0(1.2-7.2) poor tandem gait 2.7(1.1-6.2) No association: sex, living alone, physical activity, diuretic/anti depressants, alcohol, vibratory and position sense in fee, all cardiovascular findings, <24 on MMSE Nevitt and colleagues. 1991 [44] USA; (n=59) and women (n=266); >60 yrs; > 1 fall in previous year; 1 year follow-up; mean age= 70.3 yrs Weekly ascertainment Nurse examination post fall RF for Major Injury: 539 falls 58% of subjects fell at least once 40 subjects had 2 falls 68 subjects 3+ falls 6% of falls major injury 42% of subjects limited their activities as a result of 1+falls 52% of falls occurred in the subject's home 89% of falls at home happened indoors RF Adjusted OR (95% CI) Age > 80 2.0 (0.7-5.4) Women 2.0 (0.6-6.6) White 18.4 (7.5-44.6) Fall with fx. In previous yr 6.7 (2.1-21.5) Trail making Btime 180 s) 1.9(11-3.2) Hand rx time (s 0.5 s) 1.8(0.5-6.9) Visual acuity < 20/50 1.8(0.6-4.7) Fall on 'hard' surface 2.5 (0.9-7.0) CD Author, year Population Ascertainment of fall/fractures Characteristic/Risk Factors identified Incidence of fails Davies, 1996 [45] UK; cross-sectional; n=188;>65 yrs; attended ED due to fall n/a 44% of all attenders over 65 presented due to falls 26% cognitive impairment < 25 on mini mental state exam (MMSE) 31% admitted to hospital 19% unexplained falls 11% unexplained loss of consciousness (LOC) 7/36 had LOC during carotid sinus massage and denied it n/a Bell, 2000 [46] Australia; cross-sectional; n=733; >65 yrs; attended ED due to fall ED Information System Trauma registry and patient information database ED and hospital records 17.8% (803/4489)of those 65+yrs presented due to fall 39% of men (111/283) and 24% of women (110/450) had previous falls 57% admitted to hospital 4.4% (32/733) died in hospital; 10/32 due to hip fracture n/a Close, 2003 [2,15] UK; cohort (control group from PROFET RCT); n=163; S65 yrs; attended ED due to fall Follow-up by postal questionnaire at 4, 8 and 12 months Co morbid conditions Cognitive impairment: AMT Physiological measures Environmental Hazards Medication: 4+ prescribed drugs Others: falls in previous year, indoor fall, unable to get up after fall 510 falls 52% 1 +falls 26% 3+ falls -2.4 falls/person-year Paniagua, 2006 [47] USA; cross-sectional;n=11 7 (enrolled January and June); ^ 65 yrs; attended ED due to fall ED discharge ICD-9 codes ED and computerized chart review Mean age=78.4 45% >80 yrs 57% Caucasian 57% male 12% 1 + fall in previous year 43% polypharmacy 38% cognitive impairment 58% admitted to hospital 15% of charts had instructions to follow-up with GP n/a Lehtola, 2006 [16] Finland; cohort; n=555; >85 yrs; 2 yr I follow-up Bimonthly telephone calls 74% (409/555) fell 1+ over 2 years 47% 2+ fallers Mean MMSE= 24 Mean number of prescription medications= 5 1039 falls/1000 p-yrs Women 1127 falls/1000 p-yrs Men 755 falls/1000 p-yrs 2.2.5 Physiological mechanisms that maintain postural stability to prevent falling Postural stability can be defined as the ability to maintain center of mass within limits of stability [36]. Stability limits are boundaries in which the body can maintain its position without changing the base of support [36]. Postural stability requires input from sensory systems (visual, vestibular and somatosensory), integration of this input by the central nervous system (brain stem and spinal cord) and execution of coordinated muscle activity [48]. These mechanisms allow the body to maintain upright posture in the standing position and during movement [48]. The incidence of falls increases with age [11,12] and this may be partly due to deterioration in systems that contribute to postural stability [36]. I will discuss the changes associated with age in the central nervous system, the sensory system, and the musculoskeletal system. 2.2.5.1 Age-related changes in the central nen/ous system The central nervous system (CNS) integrates sensory information, selects appropriate sensorimotor responses for the musculoskeletal system, generates thought and emotion, and stores memories [48,49]. It controls coordinated movements. Age-related changes in the CNS include loss of neuronal components (connective tissue such as glial tissue), loss of neurons and declining neurogenesis. Decline in the number of neurons is associated with a decreased ability to process information. Nerve conduction velocity decreases, voluntary movements slow as do reflex times. There is reduced efficiency of signalling within neural networks and reduced adaptive capability [50]. Age-related changes in these domains likely contribute to the increased incidence of falls with age. 2.2.5.2 Age-related changes in the sensory system The afferent pathways of the postural reflexes (these reflexes allow us remain upright) come primarily from three sensory systems: vision, vestibular and somatosensory. These systems provide information to the central nervous system which, in turn, integrates this information and selects the appropriate musculoskeletal response through the efferent pathways (alpha motor neurons). Vision plays a critical role in postural stability by continually updating the nervous system with information regarding the position and movements of body segments in relation to each other and the environment [33].To permit vision, light travels through the lens and is focused on the retina. This in turn stimulates photoreceptors that transduce light stimulus into receptor potentials. Through a series of different cells and fibres the receptor potentials are received in the primary visual cortex [49]. In one study, visual acuity was inversely associated with increases in postural sway [51]. 17 There is age-related deterioration in sensitivity to contrast and colour as well as in both stereoacuity and peripheral vision [52]. With ageing, the crystalline optic lens gradually becomes less flexible, and thus, has less capacity to change shape to focus on near objects. The amount of light that reaches the retina is also reduced with age, due in part to diminished pupil size and also because the crystalline lens absorbs more light due to the formation of a cataract. Aging has also been associated with a reduction in the eye's ability to adapt to changes in illumination (for example going from a dimly lit shopping center to bright sunlight outdoors). This has been attributed to the pupil losing the ability to adjust its size, the development of cataracts, and neural changes within the retina [52]. Increased sensitivity to glare in older adults is influenced by age-related changes in the lens and corneal opacities. The prevalence of blindness and low vision increases with age [53]. Leading causes of visual impairment in older persons are cataracts, glaucoma, diabetic retinopathy, and macular degeneration. As mentioned above, cataract is a clouding of the crystalline lens [53] - this is the leading cause of low vision in seniors. It can be treated surgically [54]. Glaucoma is the pathology of elevated intraocular pressure because of an obstructed outflow of aqueous through the angle of the anterior chamber. This can damage the optic nerve and cause loss of peripheral vision and eventually central vision. Glaucoma can be managed with medications to decrease fluid production and/or aid in draining the eye. Another approach to reduce intraocular pressure is surgically [52], Diabetic retinopathy can cause either proliferative retinopathy (new blood vessels that hemorrhage into the vitreous chamber and retinal detachment) or non-proliferative retinopathy (leakage from damaged retinal blood vessels and subsequent macular edema) [52]. Laser treatment is effective preventing severe vision loss from both types of diabetic retinopathy [55]. Macular degeneration is the leading cause of blindness (as distinct from low vision) and results in the loss of central vision while the peripheral vision remains largely intact. Age-related macular degeneration (AMD) is characterized by the presence of drusen (yellow deposits of protein lipid) on the macula [53]. AMD remains a major clinical problem but therapeutic advances that reduce abnormal retinal vascularity are on the horizon [56], Each of the abovementioned age-related eye pathologies are associated with increased falls risk. This is likely because these conditions interfere with the CNS receiving information regarding the position and movements of body segments in relation to each other and the environment. Thus, the CNS cannot send accurate message to the musculoskeletal system. The vestibular system, which lies within the temporal bone of the skull, consists of three semicircular canals and the utricle and saccule. The semicircular canals, which house the semicircular ducts, detect angular acceleration during rotation of the head along three perpendicular axes [48]. The region where the three semicircular canals meet is called the vestibule. The semicircular ducts each contain receptor cells, or hair cells, in a bulge in the wall of the duct. The cupa, a gelatinous mass, cover the hair cells. When the head moves, the semicircular duct, the . semicircular canal, and the attached bodies of the hair cells all move with the head. However, the fluid in the semicircular duct tends to retain its original position, causing the hair cells to bend. At rest the hair cells release neurotransmitter at a baseline rate. When the hair cells bend, neurotransmitter is released to reflect the direction in which they bend. The utricle and saccule are responsible for detecting linear acceleration and changes in the position of the head relative to gravity. The position of the hair cells in a person who is standing is almost horizontal in the utricle and vertical in the saccule. The hair cells in the utricle and saccule are covered in a gelatinous substance which also has tiny stones -- otoliths of calcium carbonate crystals -- embedded in it. In response to any linear movement, the gelatinous substance embedded with otoliths bends the hair cells and stimulates receptor cells. When the hair cells are stimulated, this information is transmitted to the brain stem via the Vestibular Nerve (8th cranial). From here is it transmitted to the parietal lobe which is adjacent to the somatosensory cortex. The information from the vestibular system is integrated with information from the joints, tendons and skin to provide the sense of posture and movement [48]. Vestibular information is used to control eye muscle (eyes remain fixed despite changes in head position) and to provide the position and acceleration of the body. In the vestibular system, there is progressive loss of hair cells from birth [57], and this may contribute to reduced postural control with age. Sensation from the skin, muscles, bones, tendons and joints is termed somatic sensation and is initiated by a variety of somatic receptors (somatosensory system). Some of these receptors respond to mechanical stimulation of the skin, hairs, and underlying tissues and other respond to changes in temperature or chemicals. Activation of these receptors provides the sensation of touch, pressure, temperature, pain, and awareness of the position of the body parts and their movement [48]. The message from the somatic receptors is received primarily in the somatosensory cortex of the brain. The primary receptors responsible for the sense of posture and movement are the muscle-spindle stretch receptors in skeletal muscle. Muscle spindles are interspersed among regular skeletal muscles fibres (extrafusal muscle fibres) in parallel. Muscle spindles consist of a connective tissue capsule (which encloses the intrafusal muscle spindles), intrafusal muscle fibres and stretch receptors. The muscle spindles monitor changes in the length of skeletal muscle by responding to the rate and magnitude of the change in length. When either of these changes is detected by the stretch receptors, information is relayed to the cerebrum [48]. Mechanoreceptors in the joints, tendons, ligaments, and skin are also important for posture and movement. Specifically, proprioceptors exist that provide awareness of body position and of movements of parts of the body; 19 these include muscle spindles, Golgi tendon organs, joint kinesthetic receptors and hair cells in the inner ear. Afferent neurons relay information from receptors in muscles controlled by motor neurons, other nearby muscles and the tendons, joints, and skin surrounding the muscles. These receptors provide information about the length and tension of the muscles, joint movement, and the effect of movement on the skin. Proprioceptors send information to the somatosensory cortex along the posterior column-lemniscus. Impulses conducted along this pathway give rise to discriminative touch (ability to recognize the exact location of a light touch), stereognosis (ability to recognize an object based on its size, shape and texture), propriception (ability to recognize the precise positions of body parts and direction of movements), weight discrimination (ability to assess the weight of an object) and vibratory sensation (ability to sense rapidly fluctuating touch).Golgi tendon organs are proprioceptors found at the junction of a tendon with muscle. When tension is applied to the tendon, the Golgi tendon organs send information to the central nervous system. The Golgi tendon organs help to protect tendons and associated muscles from experiencing excessive tension. Joint kinesthetic receptors are located in and around the articular capsules of synovial joints. They function similarly to Golgi tendon organs by adjusting the reflex inhibition on adjacent muscles when excessive strain is placed on the joint. Age-associated muscle spindle changes include increased spindle capsule thickness, loss of the total number of intrafusal fibers per spindle, decreased spindle diameter, and local denervation [58]. Age-related changes in Golgi tendon organs have only been demonstrated in animals; one human study demonstrated a decrease in all joint receptor types in patients undergoing shoulder arthroscopy [58]. In a study by Verschueren and colleagues, men aged 18- 70 were asked to complete a dynamic joint position sense task for passive ankle plantar flexion tested at various velocities [59]. The men aged 70 years significantly deviated from the target angle and had greater variability compared with the younger men [59], Although, men aged 60-70 years also demonstrated increased variability, they were still able, on average, to attain the target angle equally well as younger men [59]. Older adults also demonstrated decreased vibration perception thresholds, resulting clinically in diminished monofilament testing [58]. 2.2.5.3 Age-related changes in the musculoskeletal system When the CNS receives input form the afferent systems, its response is mediated through the musculoskeletal effector system. The muscles generate force and produce movement and consist of three types of fibres: slow oxidative (Type I, slow-twitch, fatigue-resistant fibres), fast oxidative (Type IIA, fast-twitch A, fatigue-resistant fibres) and fast glycolytic (Type IIB, fast-twitch B, fatigable fibres) [49]. Slow oxidative fibres maintain posture and are used for endurance activities. Fast oxidative fibres are primarily used for activities such as walking and running. Fast glycolytic fibres and used primary for rapid, intense movements of short duration such as weight lifting [49]. 20 Declines in total muscle cross-sectional area begin in early adulthood [60]. There is an accelerated loss of total muscle area and a decrease in the total number of muscle fibres at approximately 50 years of age [60,61]. Between the ages of twenty and seventy, persons experience an approximate 30% decline in muscle strength and a 40% reduction in muscle area [62]. Sarcopenia is defined as having abnormally low muscle mass and strength and it is associated with ageing [63,64]. Loss of muscle mass is likely due to both fibre atrophy and the loss of fibres [62,65]. There is preferential loss of cross-sectional area of type II fibres and a more subtle loss of cross-sectional area of type I fibres [62,65]. Roubenoff and Hughes reviewed the limited longitudinal data available on aging and concluded that total body potassium, a quantity largely driven by muscle mass, declines linearly with age in Caucasian males [64]. A large cross-sectional study, the New Mexico Elder Health Survey, examined the association between physical function and sarcopenia [66]. When sarcopenia was defined as having muscle mass 2 standard deviations or more below the mean for young healthy participants, sarcopenic women and men were 3.6 and 4.1 times, respectively, more likely to report disability compared with study participants who had normal muscle mass [66]. Also, subjects who were classified as having sarcopenia were more likely to have reported falling in the previous year [66]. The causes of sarcopenia may include sedentary lifestyle [60,67] as well as neurological, hormonal, nutritional, and immunological factors [64]. Roubenoff and Hughes concluded that the single most important cause of sarcopenia is the loss of alpha motor neuron input to muscle that occurs with age [64]. In the next section I summarize the literature that describes a solution to this problem of sarcopenia and impaired postural stability. 2.2.6 Evidence for physical activity as a means of ameliorating risk factors for falls among community-dwelling older adults at increased risk for falls Impairments in strength and balance, identified in prospective cohort studies, are associated with increased risk for having at least one fall (RR 4.4, range 1.5 to 10.3 and RR 2.9 range 1.6 to 5.4) [23].These are also the most prevalent risk factors; approximately 35-55% percent of study participants had impairments in strength and 70-90% demonstrated impairments in balance [1-3,68], Physical activity, such aerobic activities (e.g., walking), balance training, strength training, exercise classes (incorporating elements of aerobic, balance and strength training) and tai chi have been suggested as intervention strategies to ameliorate these risk factors. Improving strength and balance in older persons via physical activity may reduce falls. In this section, I review randomized controlled trials of physical activity interventions in persons aged 60 years and older that measured strength and balance outcomes. Participants were enrolled in these trials because they possessed one or more known risk factors for falls: history of at least one fall in the previous year, aged 80 years and older or met pre-specified frailty criteria. Details of these studies are provided in Table 2.3. 21 These studies suggest that community based exercise programs of resistance training with machines [69] and a general exercise program (consisting of resistance training, balance training and aerobic training) [70-72] can ameliorate strength and balance in persons with risk factors for falls. Two of these studies provided transportation to and from the community centre. For example, in the RCT conducted by Hauer and colleagues, 57 women with a history of injurious falls (46% of these were hip fractures) were enrolled. This study tested a resistance training program that took place three times per week for 12 weeks. The intervention consisted of 90 minutes of resistance training and 45 minutes of functional balance training. The study supplied transportation for the participants to come to the exercise class and to return home. Although this intervention was successful in ameliorating strength and balance in this population of patients with a history of injurious falls, the way it was delivered may only be feasible in the study setting where funds are dedicated for this purpose. I identified seven randomized controlled trials of home-based exercise in persons with known risk factors for falls. The interventions delivered included lower extremity strengthening [73-76], general exercise (strength, balance and aerobic training) [77], total body strengthening [78], balance and strength training [79] and aerobic training [75]. All interventions were delivered by either a physical therapist or an exercise therapist. Four of these studies demonstrated improvements in strength [74-76,78] and one study demonstrated improvements in balance [77]. Two of these studies did not demonstrate improvements in strength or balance [73, 79]. The degree to which the physiotherapy/exercise therapist was involved in delivering the program varied widely. For example, the study by Chandler and colleagues enrolled 100 functionally impaired men and women, and randomly allocated them to receive a lower extremity strength program with Therabands three times per week for 10 weeks with a physiotherapist present at each session [74]. The authors did not report adherence but they demonstrated a 10% gain in lower extremity strength compared with the control group that demonstrated a 3% loss in strength. However, as with the community centre study highlighted in the previous paragraph, it may not be feasible to deliver physiotherapy three times per week in the wider population and thus this model may have limited potential for knowledge exchange and community uptake. I contrast this mode of delivery with that reported in the study conducted by McMurdo and colleagues [79]. Eighty-six persons aged 75 years and older with limited mobility were randomly allocated to home-based mobility and strength exercises or to health education. The home-based program was delivered by a physiotherapist over a 30 minutes session one time per week, every three to four weeks. The participant was expected to complete a series of 24 exercises on her own for 15 minutes per day, 7 days per week for six months. This study did not demonstrate a significant improvement in balance or strength. Adherence to the exercise program was not reported in this study. These two studies illustrate that the intensity with which a program is delivered may influence outcome. Although the first study discussed demonstrated significant improvements in strength and balance, a physiotherapist was present at each of the exercise sessions. In contrast, the second study delivered a more realistic program with a 22 physiotherapist and this did not result in significant changes in strength or balance. These studies suggest that both type of exercise and the mode of exercise delivery are determinants of ameliorating fall risk factors. Home-based exercise programs may offer some advantages compared with community-based programs. Home-based programs avoid the problem of having to get to the community centre, however they may also be disadvantageous because participants must perform the exercises on their own and may not be as motivated to do so as they would be in the group environment. This may have negative implications for adherence to the exercise protocol. One particular home-based strength and balance retraining program—the Otago Exercise Program (OEP) -- was developed in New Zealand. To date five randomized controlled trials have been executed with this program, two of these targeted at-risk groups: women aged 80 years and older, and one trial in persons with severe visual impairment. This physiotherapist-delivered home-based program of progressive balance and strength retraining is detailed in section 2.2.8.3.1. A meta-analysis of four OEP randomized controlled trials was published in 2002 and included 1016 persons with an average age of 82 years. The RCT protocol for each of these studies measured balance using the 4-test balance score at baseline and again at the end of the trial (trial duration ranged from 44 to 52 weeks). The 4-test balance score ranges from 0-5. The test requires the individual to attempt four different balance stances for a maximum of 10 seconds: side by side standing, semi-tandem standing, tandem standing and single leg standing. The individual is given a score of zero if he/she is unable to stand with feet in the side-by-side position for 10 seconds; a score of 1 if able to hold a side by side standing position for 10 seconds but unable to hold a semi-tandem stance for 10 seconds; a score of 2 if able to hold a semi-tandem stance for 10 seconds but unable to hold a full tandem position for more than two seconds; a score of 3 if able to stand in the full tandem position for 3 to 9 seconds; a score of 4 if able to stand in the full tandem position for 10 seconds; and a score of 5 if able to stand on a single leg for 10 seconds. The meta-analysis included 850 persons with baseline and follow-up measures of the 4-test balance score. The control group's baseline and final scores were 3.7 (1.1 SD) and 3.6 (1.1 SD) respectively. The intervention group's baseline and final scores were 3.4 (1.1 SD) and 3.7 (1.2 SD). The difference in change comparing the two study groups was 0.2 (95% CI 0.0-0.5). The change in the intervention group represents an 8% improvement in balance; however this is not statistically significant because the confidence interval includes zero. However, it remains unknown whether or not the Otago Exercise Program, delivered to persons with a history of a previous fall, might improve balance and strength. 23 To my knowledge, no published studies have tested a physical activity intervention specifically in older adults who have presented to a health care provider due to a fall. However, Liu-Ambrose and colleagues [80]and Carter and colleagues [81] studied women with osteoporosis and low bone mass, a group at high risk for fracture, and significantly improved strength [81] and balance [80] with exercise interventions. Fiatarone and colleagues enrolled 100 nursing home residents and randomised them to receive high intensity resistance training or control [82]. Participants in the intervention group demonstrated significant increases in strength, stair climbing power and gait speed. However, these studies were all undertaken in highly supervised environments (community centres and nursing home recreation room) thus, it remains unknown whether these at-risk participants would have demonstrated the same benefits in a less-supervised environment, for example in a home-based exercise program. 24 Table 2-3 Randomised controlled trials of home-based physical activity interventions and community based physical activity interventions in 'high-risk'* for falls community-dwelling populations with falls risk factors (e.g., balance and strength) as outcomes by year of publication Author Population Intervention Control Outcome Chandler 1998 [74] 100 functionally impaired men and women; 64 years and older Home-based; lower extremity strength program with Therabands; 3x/week for 10 weeks with a physiotherapist Usual care Mean age 77; increased lower extremity strength (1:10-16 % gain vs C: 1-3% loss); adverse events: NR; compliance: NR McMurdo 1995 [79] UK; n=86; >75 yrs; limited mobility; required home care s Ix/week Home-base; PT visit for 30 min every 3-4 weeks; 24 mobility and strength related exercises; illustrated on cards; 15 min 7d/week for 6 months Health education; PT visit for 30 min every 3-4 weeks; discuss exercise, diet, sleep; 6 months Mean age=82; no significant changes in TUG or chair stand; adverse event: NR; compliance: NR Jette 1996 [78] USA; 102 persons; aged 66-87; nondisabled Home-based; videotaped strengthening program; 10 exercises using Therabands; 30 minutes 3x/week for 15 weeks Usual care 10% improvement in knee extension strength in those 72 yrs and younger; Adverse event: NR; compliance: 58% (exercises performed/exercises prescribed); Sherrington 1997 [76] Australia; n=42; >64 yrs; post hip fracture Home-based stepping program; 1x/day for 1 month; given photo of self doing exercise with written description; PT visit 2x during month (baseline + 7-days post baseline) Usual care mean age=?; increased quadriceps strength, increased gait velocity, no change in balance; compliance: 25/30 days; adverse events: none Brown 2000 [72] 84 men and women; aged 78 years and older University exercise facility; 22 exercises challenge flexibility, balance, body handling, reaction time, coordination and strength; 3x/week for 3 months Home-based exercise program; 9/22 core exercises; ?freq; 1x/month attended class at university Mean age 83; improved physical performance test) knee flexion/knee extension/Berg balance/obstacle course time; adverse events: NR; compliance: NR Author Population Intervention Control Outcome Hauer2001 [69] Germany; 57 female geriatric patients with history of injurious falls; 75 years and older Geriatric rehabilitation unit; resistance training with machines (90 min) and functional balance training (45 min); 3x/week for 12 weeks; supervised; 4-6 pts/grp ; provided transportation to exercise Geriatric rehabilitation unit; motor placebo training (flexibility, callisthenics, ball games memory tasks)(30 min); 3x/week for 12 weeks; provided transportation Mean age 82; intervention improved strength, gait speed, balance; 1:45% fell once/ C: 60% fell once; adverse events: none; compliance: 85% 74% had fractures; 46% hip fractures; clear assessment of adverse events Binder 2002 [71] 115 men and women; aged 78 years and older University exercise facility; 3x3-month phases (cardio, balance, strength); 36 sessions of each phase before moving to next phase; 3x/week for ~9 months; provided transportation as needed Home-based exercise program; low intensity 9/22 core exercises from phase 1; 2-3x/week; 1x/month attended class at university; provided transportation as needed Mean age 83; improved physical performance test/knee flexion and extension torque/1 leg stand time/V02 max/functional status/Berg balance; adverse events: 2 shoulder injuries (dropped out); compliance:l=100%/C=?? King 2002 [83] USA; 155 persons; aged 70 yrs and older; mobility impairments Three 6-month long phases (supervised group training; supervised group and home training; unsupervised home training); focus on strength, endurance, balance, flexibility; 75 min 3x/week for 18 months Home-based aerobic exercises; 1 instructional session; 180 min per week Mean age 77; 20% drop-out; improved MacArthur battery, gait speed, standing balance time @ 6 months; no differences between groups @ 18 months; adverse events: 9/93 related to exercise; compliance: first 6 months 1=61% and C=51%, months 16-181=22% and C=19% Latham 2003 [73] New Zealand;243 men and women admitted to geriatric rehabilitation (in and out patient); frail; 65 years and older Home-based; quadriceps strengthening program with ankle weights; 3x/week for 10 weeks; PT alternated between home visits and phone calls each week Usual care Mean age 79;no change in quad strength, Berg balance, timed walk, falls; adverse events: increased risk of MSK injuries attributed to EX; Compliance: 82% (25/30) Unclear what proportion community-dwelling; clear assessment of adverse events <y> Author Population Intervention Control Outcome Lord 2003 [84] Australia; 551 men and women; assisted living; 62 years and older Common room at assisted living residence; exercise program that targeted falls risk factors and ADLs (60 min); 2x/week for 12 months; supervised Common room at assisted living residence; flexibility and relaxation (60 min); 2x/week for 12 months; supervised OR Usual care Mean age 79; 22% reduction in falls risk, improved reaction time/choice stepping rx time/6-min walk, no change in strength/balance; adverse events: NR; compliance: 42% Exercise class scheduled so not to conflict with other activities; ?trend for balance to worsen over time Papaioannou 2003 [77] Canada; 74 women; aged 60 yrs and older; dx osteoporosis Home-based; 1 hr training session; stretching, strength training and aerobics; manual with diagrams; Therabands; 60 min throughout day; 3x/week for 12 months; exercise therapist visit 1x/month for 6 months; telephone call every 2 weeks for 12 months Usual care Mean age 72; improved quality of life; no difference in TUG; improved balance; Adverse events: NR; Compliance: 62% completed 3x/week for at least 80% of weeks @ 6 months and 46% at 12 months Suzuki 2004 [70] Japan; 52 women; 73 years and older Community center; stre n g th/ba I a n ce/g a it/res ista n ce/ta i chi (60 min); 1x every 2 weeks for 6 months; supervised Home-based, 15 exercises learned at community center (30 min), 3x/week for 6 months Usual care + pamphlet on falls Mean age 79; improved quad strength/tandem walk/functional reach; adverse events: NR; compliance: 75% for community centre, NR for home-based ?analysis Mangione 2005 [75] USA; n=41;£65 yrs; post hip fracture Aerobic: home-based; 65-75% of max hear rate for 20 minutes; 20 exercise instructor visits Resistance: home-based; PT delivered; 30-40 min 2x/week for 2 months; 1x/week for 1 month; progressive resistance exercise machine targeting lower extremity strength; 20 PT visits Biweekly mailing of healthy ageing material Mean age-78; improved isometric lower extremity strength in both intervention groups cf control; adverse events: 1 subject fell, many had muscle soreness; compliance: 98% *high-risk defined as participants meeting a pre-specified frailty criteria; history of at least 1 fall in previous year; hx of fracture; aged 80 years and older; assisted living PT= physiotherapist; l= intervention; C= control; NR= not reported; TUG=Timed up and Go; r-o 2.2.7 Measurement of falls risk factors and falls In section 2.2.5,1 reviewed the physiological mechanisms that underpin age-associated pathogenesis in balance control systems which lead to falls. In this section, I address the question of how researchers (and clinicians) might quantify those changes in clinical studies. 2.2.7.1 Measurement of falls risk factors 2.2.7.1.1 The Physiological Profile Assessment The Physiological Profile Assessment (PPA) is a falls risk assessment tool and is available in two formats: "long-form" and "short-form" [41]. The long-form consists of 16 tests from 6 domains: vision (high/low contrast visual acuity, edge contrast sensitivity), vestibular function (visual field test), peripheral sensation (tactile sensitivity, vibration sense, lower limb proprioception), muscle force (knee flexion, knee extension, ankle dorsiflexion), reaction time (hand and foot) and balance (eyes open and closed on firm and compliant surfaces). In a discriminant function analysis, five tests correctly distinguished between multiple (two or more falls) and non-multiple (zero or one fall) fallers [13]. These five tests (from five different domains) constitute the "short-form": edge contrast sensitivity, hand reaction time, lower limb proprioception, knee extension strength and sway on a compliant surface with eyes open. The short-form tests are described in detail in Table 2.4. The PPA correctly distinguishes multiple fallers (2 or more falls) from non-multiple fallers (0 or 1 fall) in 75% of cases (sensitivity=75%; specificity= 75%; positive predictive value (PPV)=44%; negative predictive value (NPV)=92%) [13, 85], Data from the PPA components are entered into a Web-based software program (https://www.powmri.edu.au/Falls/slintro.asp). A weighted z-score is calculated for each component and these are summed to provide an overall falls risk z-score. The weights for each component are reported in Table 2-3. The z-scores for each component of the PPA are calculated using the means and standard deviations measured from two Australian cohort studies for persons who were non-multiple fallers (0 or 1 fall during one-year follow-up) [13,85] (please see Table 2.5 for study details). These two studies enrolled community-dwelling men and women aged 60 years and older with one-year prospective follow-up to measure the incidence of falls [13, 85]. The PPA components are reliable (test-retest) and these coefficients are documented in Table 2-3. The PPA literature states that 15-20 minutes are needed to administer the tests [41]. However, in a randomized controlled trial that enrolled women with low bone mass, the time to complete the PPA assessment ranged from 20-30 minutes [80]. In total, the PPA short form hardware and a licence to access the software costs $5 000 (CDN). Several randomized controlled trials of physical activity have measured falls risk using the Physiological Profile Assessment (PPA) and the PPA appears to be sensitive to change in response to an intervention—an important test 28 characteristic (Table 2.6) [80,84,86-89], For example, in a randomized controlled trial of women aged 75-85 with low bone mass, agility training and strength training significantly reduced PPA z-score by 48% and 57% respectively, compared to stretching control which only decreased by 20%. There have been five randomized controlled trials to date (all interventions have included a physical activity component) that have measured PPA z-score and its sub-components at baseline and follow-up as well as the occurrence of falls [84, 86-89], Although all five RCTs have reported significant improvement in at least one of the five domains of the PPA, the relationship between improvement in the PPA z-score, its sub-components, and falls prevention was not as straightforward as one might have anticipated. For example, two studies did not demonstrate a significant reduction in falls [86,87] despite improvements in strength [87], reaction time [87], sway [87] and vision [86]. In three studies the rate of falls decreased in the intervention group, but the sub-components of the PPA did not change consistently across these studies: sway [89], quadriceps strength [88] and reaction time [84]. Therefore, although the PPA and its sub-components are responsive to change associated with physical activity interventions the relationship between PPA change and falls is not clear. The PPA has many assets. It is simple to administer, has a short administration time, is feasible for older people to undertake, consists of valid and reliable measurements, is portable, provides quantitative continuous measurements for all tests, and can accurately distinguish between multiple and non-multiple fallers [41]. The PPA, however, does not directly assess several risk factors for falls such as depression, cognitive impairment, adverse effects of psychoactive medications, aspects of medical conditions such as Parkinson's disease, stroke, lower-limb amputation, postural hypotension and vestibular disease [41]. Nevertheless, some of these risk factors may manifest indirectly through performance on the tests (e.g., benzodiazepine use and impaired reaction time). Therefore, it has been suggested that the PPA should complement a medical examination. The PPA can help identify impairments and the persons' medical history can provide context to best tailor individual interventions. The properties of the PPA discussed in this section make it a suitable instrument to assess risk factors for falls and measure changes that may result from an intervention. This instrument provided the primary outcome for my randomized controlled trial (Chapter 4). Although there are several other instruments that could have been used to assess risk factors for falls, they do not provide such a comprehensive evaluation of the domains that contribute to falls risk (vision, strength, proprioception, reaction time and sway). To add depth to this section of the literature review, I also discuss the Timed Up and Go test (a performance measure), other performance measures, force plate technology and the Berg Balance Score. 29 Table 2-4 Physiological Profile Assessment test descriptions, canonical regression weight and intraclass correlation coefficient (ICC) Test Name Test Description [13,41] Coefficient*[13] ICC (95% Cl)[41] Edge Contrast Sensitivity (ECS) ECS is assessed using the Melbourne Edge Test which contains 20 circles each with edges of reducing contrast. Participants are asked to correctly identify the direction of the line that divides the circles' low and high contrast halves (vertical, horizontal, 45 degrees left, 45 degrees right). The lowest contrast circle correctly identified is recorded as the participants' contrast sensitivity. -0.33 0.81 (0.70-0.88) Lower limb proprioception Proprioception is assessed using a lower limb matching task. Participants are seated with their eyes closed and are asked to align their lower limbs simultaneously on either side of a vertical clear acrylic sheet inscribed with a protractor and placed between their legs. The difference between the great toes on either side of the sheet is measured in degrees. The participant is given 2 practice trials and then the average of 5 experimental trials is recorded. 0.20 0.50 (0.15-0.74) Knee Extension Strength (KES) Maximal isometric knee extension strength (kilograms) is tested using a spring gauge attached to the participant's leg using a strap with a Velcro fastener. This test is performed with the subject seated in a tall chair with the strap approximately 10 cm above the ankle joint, with the hip and knee joints positioned at 90 degrees. This test is repeated 3 times and the best effort is recorded. -0.16 0.97 (0.93-0.98) Hand Reaction Time Hand reaction time (milliseconds) is assessed using a hand-held electronic timer with a computer mouse attached. The light stimulus is adjacent to the response switch. The participant is instructed to press their finger down on the mouse switch as fast as soon as they see the red light stimulus. 0.47 0.69 (0.45-0.84) Postural Sway Postural sway is measured using a sway meter that records displacements of the body at waist level. The sway meter consists of a 40 cm long rod with a vertically mounted pen at its end. The rod is attached to the subject by a best and extends posteriorly. The participant is instructed to stand as still as possible for 30 seconds under four different conditions: (a) eyes open on a firm surface, (b) eyes closed on a firm surface, (c) eyes open on medium-density foam rubber mat and (d) eyes close on a medium-density foam rubber mat. Over the course of 30 seconds the pen records the participants' sway on a sheet of millimetre graph paper fastened to the top of an adjustable table. 0.51 a) 0.68 (0.45-0.82); b) 0.85 (0.72-0.92); c) 0.57 (0.30-0.76); d) 0.83 (.69-.91) Canonical correlation coefficient for discriminant function model oo o Table 2-5 Observational studies that used the Physiological Profile Assessment (PPA) and/or its sub-components as outcome measures Author Study Design and duration Population Outcome Measures Results Lord 1991 [43] Australia; Cohort study; 12 months n=95 men and women aged 59-97 Hostel for Aged Persons (similar to assisted living in CDN) Falls Physiological measures: Visual acuity Edge contrast sensitivity Touch threshold at the ankle vibration sense at the knee lower limb proprioception vestibular stepping test vestibular optical stability quadriceps strength ankle dorsiflexion strength reaction time body sway on firm and compliant surfaces static balance dynamic balance Falls: 145 falls Physiological measures: multiple (s 2 in 12 months) fallers had reduced contrast sensitivity, decreased proprioception, slower reaction time, increase sway on floor with eyes closed, increased sway on foam with eyes open and closed compared to non-fallers and those that fell only once Quads and ankle dorsiflexion strength were not significantly worse compared with non- and 1-time fallers Discriminant function: contrast sensitivity, proprioception, ankle dorsiflexion strength, reaction time and sway with eyes closed discriminated btw multiple fallers and non-multiple fallers (correctly classified multiple and non-multiple fallers 75%) Age not included in discriminant function—less important contributor to discriminating between multiple fallers and non-multiple fallers than the test measures (but age has indirect effect via association with the test measures) Author Study Design and duration Population Outcome Measures Results Lord 1994 [13] Australia;cohort study; 12 months n=373 women >65 yrs Community-dwelling Falls Vision, lower limb muscle strength, reaction time and balance Falls: 134/371 (39%) reported >1 fall; 287 falls total -0.8 falls per person-year Physiological Factors: multiple fallers performed sig. worse than non-multiple fallers on ECS, visual acuity, proprioception, vibration sense, quadriceps strength, ankle strength, reaction time and all measures of sway (eyes open/closed on firm/compliant surfaces) Discriminant Function: ECS, proprioception, quadriceps strength, reaction time, sway eyes open on compliant surface (discriminated significantly between multiple fallers and non multiple fallers); correctly classified 74% of the cases Age was not controlled for in this study (for discriminant function analysis) - less important contributor to discriminating between multiple fallers and non-multiple fallers than the physiological measures Lord 1994 [90] Australia; cross-sectional study; N=1762 Men and women Community-dwelling (32 were nursing home) >60 yrs Postural stability Retrospective assessment of falls history Retrospective assessment of fracture history Psychoactive medication history Postural stability: age associated declines in sway (eyes open/close on firm/compliant surface), quadriceps strength, touch; men cf to women performed significantly better in quadriceps strength, sway on floor with eyes open; multiple fallers compared with non multiple fallers had weaker quadriceps, and greater sway with eyes closed on a firm surface and eyes open/closed on compliant surface Postural stability and history of fracture: weaker quadriceps and greater sway on foam with eyes open than those who did not fracture Psychoactive medication: significantly associated with being a multiple faller; use associated with reduced tactile sensitivity and poor dynamic balance; in women associated with reduced quadriceps strength, increased sway on foam with eyes open and closed Salter 2005 [91] Canada; cohort study; 6 months N=54 >60 yrs Community-dwelling Presented to ED with a fall and discharged back to community Elements of guideline care received within 6 months PPA Guideline Care: 2/54 (3.7%) received AGS guideline care PPA: baseline PPA score 1.7 and significantly increased to 2.2 over 6 months (sway on foam eyes open, quadriceps strength, proprioception, reaction time, edge contrast sensitivity all significantly worsened over 6 months) c o r o Author Study Design and duration Population Outcome Measures Results Szabo 2006 [92] Canada; cross-sectional study AMD group: N=115 women, S70 yrs, AMD, community-dwelling Friend controls: N=54, >70 yrs, community-dwelling Australian controls: n=341; community-dwelling, s65yrs PPA PPA: AMD group PPA z-score 3.26 (1.26); Friend controls 0.89 (0.79); Australian referent population 0 (1); AMD group performed significantly worse on all 5 sub-components compared with both control groups Foley 2006 [93] Australia; cross-sectional study N=850 Men and women Aged 50-80 yrs Community-dwelling WOMAC PPA Knee/hip ROM WOMAC score and falls risk z score significantly related for trend (higher WOMAC, increased falls risk) PPA z score: male (0.09); female (0.27) Relatively low risk group compared with other studies AMD: age-related macular degeneration, ED: emergency department, WOMAC: Western Ontario and McMaster Osteoarthritis Index O O oo Table 2-6 Randomized controlled trials (RCT) that used the Physiological Profile Assessment (PPA) or its sub-components as an outcome measure Author Study Design and duration Population Intervention Control Outcome Measures Results Lord Australia^ 2 N=179 1. Community group based exercise (2x/wk, 60 Usual care Falls, balance, Compliance: 73% 1995 months Women minutes) reaction time, (60/82) [87] >60 neuromuscular Falls RF: all measures Community-dwelling 1. control, muscle strength of strength, reaction times, neuromuscular control, sway (eyes open firm and eyes open/closed compliant) Falls: exercise did not significantly reduce the proportion of women who fell at least once Author Study Design and duration Population Intervention Control Outcome Measures Results Day 2002[88] Australia; factorial design (8 groups); 18 months N=1090 Men and women >70 Community-dwelling 1. 1. Group based exercise (1x/wk; 60 min; 15 weeks + daily home exercises 12 months): strength and balance class 2. Home hazard management: removed or modified by participants or by city Vision improvement: referred to ophthalmologist, gp or optician Usual care Falls Exercise compliance: 67% (10/15) and avg 9 (= 2x/wk) at-home sessions/month for 12 months Home hazards compliance:76% (363/478) Vision compliance: 96% (97/101), resulted in 26 receiving tx RF for falls: quadriceps strength improved in the exercise intervention cf all others; max balance range stabilized in the exercise group and declined in the others Falls: exercise alone decreased the time to first fall (0.82 95% CI 0.70-0.97); exercise plus vision plus home hazard (0.67 95% CI 0.51-0.88) co Author Study Design and duration Population Intervention Control Outcome Measures Results Barnett Australia; 6 N=163 3. Group exercise (1x/wk; 60 minutes) with Usual care Falls, physical Compliance: 23/37 2003 and 12 Men and women ancillary home exercise (based on class performance (62%); 90% completed [89] months >65 content): exercises designed to improve measures exercise at home Community-dwelling 'At risk' by standardized assessment by GP or PT balance, coordination, aerobic capacity, muscle strength, functional exercises (sit to stand, weight transference and reaching). 1x/wk; 13% completed them daily Falls: exercise (0.61 falls/p-yr) and control (0.95) IRR 0.60 (95% CI 0.36-0.99) Performance measures: exercise group cf. control significantly improved sway on floor with eyes open and closed and coordinated stability task; no improvement in knee extension strength, reaction time, gait speed.fear falling CO Author Study Design and duration Population Intervention Control Outcome Measures Results Lord Australia; N=551 Group exercise (GE) (2x/wk, 60 min): addressed 1. Flexibility Falls, Choice Falls: GE (0.67 falls/p-2003 Cluster; 12 Men and women strength, speed, coordination, balance and gait and, and stepping reaction yr )cf all controls (0.85 [84] months >60 targeted at ADLs such as balancing while turning relaxation time, falls/p-yr) HR 0.78 (95% Retirement and reaching, rising from a chair, negotiating stairs, class 6-min walk ci 0.62-0.99); villages maintaining balance in standing and walking (2x/week, distance, Compliance: Group conditions that challenge balance, making fast and 60 min): all Postural sway, exercise 42%; flexibility appropriate balance corrections exercises in Leaning balance, 45% seated simple reaction Physical performance position time, lower limb measures: GE cf all 2. Usual care strength controls significantly improved simple reaction time, choice stepping reaction time and 6-min walk distance; no significant improvements in balance or strength Author Study Design and duration Population Intervention Control Outcome Measures Results Liu-Ambrose 2004 [80] Canada; 3 groups; 6 months 2. n=98 3. women 4. aged 75-85 5. low bone mass community-dwelling 2 interventions (2x/week; 50 min): 2. Resistance training (RT): community center based; progressive high intensity using Keiser equipment 4. Agility training (AT): community center based; class challenged hand-eye/foot-eye coordination, dynamic balance, standing and leaning balance and reaction time Stretching (sham) exercise (2x/wk; 50 min): stretching and deep breathing exercises PPA and sub-components of the Community Balance and Mobility Scale Compliance: resistance (85%); agility (87.3%); stretching (79%) PPA:RT (2.2 to 1.0) and AT (2.4 to 1.7) significantly decreased PPA score vs control (1.9 to 1.5) Sub components: RT (230.1 to 160) and AT (219 to 155) improved postural sway vs control (217 to 217); no group differences for knee extension strength t o o o Author Study Design and duration Population Intervention Control Outcome Measures Results Lord Australia; 3 2. n=620 2 interventions: Control group PPA falls risk Compliance: Exercise 2005 groups; 6 3. men and 1. Extensive intervention group (EIG): (CG) received score and EIG 21/78 (27%); [86] and 12 women individualized interventions comprising of: no intervention, subcomponents Vision: EIG: 67%; MIG: months 4. >75 a) Exercise: community based; 2x/week; at the end of the 5x Sit-to-Stand 53%-77%; Sensation: 5. Community- strength/balance/flexibility/coordination (30 study received test EIG: 46-75%; MIG: 36-dwelling min) + individualized exercises targeting MIG Falls 76% limitation (10 min) PPA:EIG (-0.242 + b) strategies for max. vision: referral to eye 0.77) reduced PPA specialist; new glasses as req, use of score vsCG(-0.118 ± single lens spectacles, cataract surgery; 0.76) counseling strategies PPA-subcomp: no c) strategies for max sensation: counseling difference between about impaired peripheral sensation groups in knee 2. Minimal intervention group (MIG): received brief extension strength, advice including: instruction sheets for home reaction time and all exercises with brief training session and list of balance tests group exercises available near home 5x sit-to-stand: EIG (-2 s) and MIG (-1.3 s) had significantly faster STS time than the CG (-0.4 s) Falls: CG rate (0.87 falls/p-yr); EIG (0.91 falls/p-yr); MIG (0.78 falls/p-yr); cftoCG: IRR EIG=1.03 (0.78-1.35); IRR MIG= 0.9 (0.69-1.17) cf: compare c o C D 2.2.7.1.2 Timed up and go test The "up and go" test was validated by Mathias and colleagues in 1986 [94]. To complete the up and go test, the subject rises from a chair, walks 3 meters, turns around, walk back to the chair and sits down. The purpose of the original test was descriptive and allowed clinicians to evaluate how well a patient could perform this activity on a five-point scale. It was validated using laboratory measures of balance. The "timed" component was added to the "up and go" test by Podsiadlo and colleagues [95] .The time up and go (TUG) takes less than five minutes to administer. In a cross-sectional study, Shumway-Cook and colleagues compared the time to complete the TUG under three different conditions in 15 participants who had a history of falls (2 or more falls in the previous 6 months) and 15 participants without a history of falls: TUG, TUG manual (while carrying a glass of water) and TUG cognitive (while subtracting three from a randomly chosen number between 20 and 100) [96]. This study demonstrated that the fallers, on average, took longer to complete the TUG under all three conditions compared with the non-fallers [96]. The TUG had 87% sensitivity and 87% specificity, and the TUG manual and cognitive demonstrated 80% sensitivity and 93% specificity [96]. A TUG cutoff level of at least 13.5 seconds correctly classified participants as fallers in 90% of cases [96]. A more recent cross sectional study comparing TUG times between community-dwelling (n=413) and institutionalized elderly women (n=73), suggested that community-dwelling women aged 65-85 years should be able to perform the TUG test in 12 seconds or less. A performance time greater than this indicates impaired mobility and may be used to determine which patients should be referred for an in-depth mobility assessment and intervention [97]. UK physiotherapist Julie Whitney and colleagues assessed the TUG time, cognitive function, and PPA in 110 consecutive patients who sought medical care after a fall [98]. Setting a cut-point of 15 seconds provided 81% sensitivity and 39% specificity in classifying patients as having a PPA score at least 2 (indicating marked risk) [98]. Using the TUG and this cut-point as a screening measure would lead to 70% of the sample being identified as needing the more detailed PPA assessment [98]. Although the TUG is a simple test of balance and mobility that can be performed in the clinical environment, it does not provide a comprehensive picture of the components that contribute falls risk. However, this test is valid, reliable and is used frequently in geriatric medicine practices; therefore it was included in the series of baseline balance assessments in the randomized controlled trial (Chapter 4). Change in TUG time is a secondary objective of the RCT. 2.2.7.1.3 Other physical performance tests Many other clinical tests have been proposed to discriminate between fallers and non-fallers. Some of the more commonly-used are standing balance tests (parallel, semi-tandem, tandem, single-leg) and gait speed [99,100] .The 40 standing balance tests require the participant to maintain stance with progressively smaller bases of support (parallel, semi-tandem, tandem, single-leg) for 10 seconds. These tests can be evaluated as a simple dichotomy able and unable, or by recording the time the participant was able to sustain the position to a maximum of 10 seconds. The measure of gait speed assesses the time it takes the participant to walk a predetermined distance. In the chair stand test asks the participant stands from the seated position without using their arms. If this can be done successfully, the participant is timed while performing the sit to stand task five times. Each of these tests takes less that a minute to administer and has no associated equipment costs. Vellas and colleagues in a 3-year longitudinal study of 316 community-dwelling adults (mean age = 73 years) demonstrated that the inability to stand on one leg for 5 seconds was a significant predictor of injurious falls, but not of all falls [101]. Inability to stand on one leg was associated with increased falls risk in a longitudinal study of 336 men and women aged 75 years and older [11]. In a cross-sectional study of 3 075 high functioning Caucasian and African-American aged 70-79 living in the community, slow gait speed, difficulty standing from a chair, and decreased balance time (semi-tandem-tandem stand score) were associated with a history of falls [102]. Inability to rise from a chair predicted future falls [11,12]. Inability or prolonged time to rise from a chair without using the arms (>2 seconds) predicted injurious falls [44] and recurrent falls [14] in a cohort of 325 community-dwelling men and women aged 60 years and older. The performance measures, similar to the TUG, are simple to administer in the clinical environment and do not require specialized equipment to undertake the test. Like the TUG, these tests do not provide a comprehensive measure of the variables that contribute to falls risk. Their main role is in office screening ~ helping to identify patients who are appropriate for a more detailed, and likely time- and resource-intensive, assessment. I was interested in the effect of physical activity on the domains of strength and balance, and these'tests do not specifically measure these. 2.2.7.1.4 Force platform A Sensory Organization Test (SOT) can be performed using computerized dynamic posturography equipment (EquiTest, NeuroCom, Clackamas, Oreg, USA). The SOT consists of tests of balance performed under six conditions: fixed platform (eyes open, eyes closed and vision sway-referenced) and sway-referenced platform (eyes open, eyes closed and vision sway-referenced). In a recent cohort study of 206 healthy community-dwelling volunteers, the last condition of the SOT (inaccurate somatosensory and visual input) predicted multiple fallers over a 16 month follow-up period [103]. To my knowledge, there are no reports of sensitivity and specificity of the SOT for prospectively predicting fallers from among a community-based cohort of seniors. It takes approximately 30 minutes to administer the SOT and the instrument costs $ 200 000 (USD). 41 The SOT is useful for evaluating the relative contributions of visual, vestibular and somatosensory inputs to maintain balance. However, the SOT is a large (therefore not portable) expensive instrument that is not readily accessible to clinicians in everyday practice. Although it is designed to address the input of various systems to upright posture, it seems to address the balance system primarily; it does not quantify important factors such as strength, visual acuity/contrast sensitivity and reaction time. An additional and important limitation of the SOT testing is that frail participants feel concerned for their safety while performing the test (personal communication, Liu-Ambrose, February 24,2007). If this anxiety manifested as participants not returning for follow-up measurements, it would be a major deterrent to investigators using this instrument for longitudinal observational and intervention trials. 2.2.7.1.5 Berg balance scale The Berg balance scale, invented by Professor Kathy Berg from the University of Toronto, is a very well-known clinical test originally designed to evaluate fall risk in those who had had a stroke but now widely-used as a measure of functional balance. The test forms part of the core curriculum of assessments taught to physical therapist and occupational therapists in many parts of the world. The scale score is calculated by scoring 14 tasks on a 5-point ordinal scale (0=unable to performs, 4= independent) [104,105]. The score for the 14 tasks are summed and result in a score ranging from 0-56, where a higher score indicates better performance. A Berg Balance Score of less than 45 was shown to predict recurrent falls [106]. A recent study, however, demonstrated that the Berg Scale did not accurately categorise multiple fallers [107]. It was suggested that perhaps the Berg had a ceiling effect as many of the multiple fallers performed well on the BBS. It takes approximately 15-20 minutes to administer the BSS, costs nothing and requires equipment that is easily accessible in the clinical environment. The BSS is an inexpensive method to assess a person performing 14 functional activities. As highlighted above however, there may be a ceiling effect with this measure as it has had varying results in predicting falls [107], I did not use the Berg Balance Scale for this reason and because I was interested in the different parameters that contribute to falls risk—balance and strength. 2.2.7.2 The measurement and statistical analysis of falls In this section I overview research methods used to measure falls and briefly describe several issues regarding the statistical analysis of falls. 42 2.2.7.2.1 Measurement of falls A fall in this thesis is defined, using the Kellogg International Working Group definition, as "unintentionally coming to the ground or some lower level and other than as a consequence of sustaining a violent blow, sudden onset of paralysis as in stroke or an epileptic seizure" [108], What further increases the challenge of measuring falls is how researchers define a fall. This definition has been broadened in some studies to include falls where dizziness and syncope are implied as part of the causal pathway. The former definition is appropriate for studies that aim to identify factors that impair sensorimotor function and balance control, where the broader definition is appropriate for studies that attempting to address cardiovascular causes of falls (e.g. carotid sinus, transient ischaemic attacks) [36]. In the randomized controlled trial (Chapter 4), I will use the Kellogg International Working Group definition. Falls are challenging events to measure because the majority are unwitnessed events and often do not result in the individual presenting for medical attention [109]. The majority of injuries are minor events (from a physical injury perspective) and are treated in the home. The injury pyramid demonstrates where the relative proportion of injuries are treated (Figure 1). Thus, when falls are monitored in older individuals, the greatest number of falls will occur in the home and will not require medical attention and this is supported by the literature [14,110]. Falls are not reportable and it is necessary to rely on the individual to report. 43 Figure 2-1 The injury pyramid Earlier work in falls research asked participants to recall the number of falls they have had over a given period of time. However, this method has been replaced by a diary/calendar method for prospective recording of falls over the study period. Two studies provide evidence for the superiority of the diary/calendar method compared with recall for falls [111,112]. Cummings and colleagues conducted a prospective study to assess the incidence of falls in a population of older adults. Participants were asked to monitor their falls on monthly calendars and to submit these to the study personnel at the end of each month for one year. At the end of the study participants were asked to recall how many falls they had sustained in the previous 3,6 and 12 months. The falls reported by recall were compared to those documented in the monthly calendars. The results of this study demonstrated that recall at 3,6, and 12-months underestimated the number of falls compared to the use of a calendar. Recall likely underestimates the number of falls by 13-32% [111]. Interestingly, the shorter the recall period, the less likely individuals were able to recall a fall [111]. The authors postulated that non-study populations are likely to be underestimate falls, as assessed by recall, to an even greater degree as the individuals in this study were under intense surveillance and follow up [111]. In a more recent study, Peel enrolled 252 Australians aged 51 to 87 years [112]. They were asked to prospectively record falls using a calendar and to mail it to study personnel at the end of each month. At the end of the study, participants were asked to recall how many falls they had during the previous year. Peel reported that over one third of individuals, who reported any fall prospectively, did not recall the number of falls when interviewed at the end of the study [112]. Participants who sustained a fall-related injury were more likely to remember falling (87%) compared to those who did not sustain an injury (62%). Furthermore, the accuracy of recall at 12-months decreased with increasing number of falls recorded prospectively [112]. 44 Although diaries appear to give a more accurate count of falls compared to recall, both measures rely entirely on self-report. Therefore, the potential for under-reporting and over-reporting of falls exists, even in the diaries/calendars. Cumming and colleagues, in their discussion of methodological issues for falls state: "Since falls are often unwitnessed events and much important information about the fall can only be obtained from the person who falls, self-report is a critical source of data on falls" [109]. Although, investigators may not be able to witness the events, there may be individuals who will witness the fall, or at least will be able to substantiate the claim. Lord and colleagues conducted a cohort study to measure the incidence of falls in older persons residing in a 'hostel for the elderly'. The investigators asked the nursing staff at the hostel to keep a 'falls log' at the nursing station and the participants were asked to record their falls in monthly calendars. The 'falls log' method was only introduced for those participants who were deemed to be cognitively impaired and therefore potentially unreliable. In this study, implementation of the 'falls log' increased the number of falls from 110 to 145 and resulted in four subjects being classified as fallers rather than non-fallers [43]. The results of this study suggest that, when possible, collateral information about fall events should be obtained whenever possible. Again, the challenge becomes trying to ascertain the falls that were not witnessed, were not recorded and that were not reported to another individual. As yet, the recording of falls remains an imperfect measure, and the self-report diary is viewed as the gold standard. 2.2.7.2.2 Statistical analysis of fall events Falls pose an interesting analytic challenge to researchers as they are events that can occur more than once over the period of observation. Traditional survival analysis, such as Cox proportional hazards, considers only the first event and ignores all subsequent events. This approach has limited utility because an intervention to reduce falls may not impact the first event but rather subsequent events. In that case, only counting the first event may incorrectly lead investigators to conclude that an intervention is ineffective, when in fact the opposite is true. These questions are articulated in "gaps in current knowledge" section of my literature review and, as mentioned above, form the basis of Chapter 5 of my thesis. 2.2.8 Falls Prevention Interventions In this section I will focus on physical activity as an intervention strategy to prevent falls but I first summarize what is known about the protean intervention strategies to prevent falls. They include additional medication (vitamin D supplementation), reduction of medication (psychotropic medication withdrawal), more aggressive medical intervention with pacemaker and cataract surgery, as well as the intervention of occupational therapists to adjust the home environment. 45 2.2.8.1 Vitamin D supplementation,psychotropic medication withdrawal, cardiac pacing, interventions to improve vision and home environment modification Vitamin D supplementation is a low-cost intervention that may prevent falls in older adults. The Nottingham Neck of Femur Study enrolled 150 persons post-hip fracture surgery that, prior to the fracture, were community-dwelling. Participants were randomly allocated to receive a single injection of 300,000 units of vitamin D2, injected vitamin D2 plus 1 g/day oral calcium, 800 units/day oral vitamin D3 plus 1 g/day calcium, or placebo. All groups receiving vitamin D pooled had a reduced risk of falls compared with placebo control group (RR 0.48 95% CI 0.26-0.90) [113]. In a 2004 randomized controlled trial, 378 community-dwelling Swiss persons aged 70 years and older were randomly allocated to receive 1 microgram of alfacalcidol (a form of vitamin D) or to placebo control. Alfacalcidol was effective in reducing the number of fallers only when calcium intake was greater than 500 mg daily [114]. Withdrawal of medication is also part of falls prevention strategy. Only one randomised controlled trial to date has examined the effectiveness of psychotropic medication withdrawal on preventing falls. This trial was conducted in New Zealand and enrolled 93 persons aged 65 years and older currently taking psychotropic medication [115]. Participants were randomized to one of four groups: psychotropic medication withdrawal, physiotherapist-delivered home-based balance and strength retraining, both intervention, and neither intervention. Persons who received psychotropic medication withdrawal compared to those who did not receive this intervention reduced the risk of falls by 47% (0.34-0.74). Although the trial was successful, 47% of participants resumed taking their psychotropic medication after the study was completed [8,115], Medical management to prevent falls can involve cardiac pacing. I the UK-based SAFE PACE I study, 175 people aged 50 year and older who presented to the emergency department with an unexplained fall were randomized to receive a dual chamber pacemaker or to usual care [116]. This study demonstrated a 58% (OR 0.42 95% CI 0.23-0.75) reduction in falls in patients who received a dual chamber pacemaker compared to usual care [8,116]. Surgery can improve impaired visual acuity and poor contrast sensitivity that are risk factors for falls [13,33]. A randomized controlled trial of expedited first eye cataract surgery was associated with a 34% reduction in the rate of falls (IRR 0.66 95% CI 0.45 0.96) [117]. The authors also report the time to first fall (Cox proportional hazards), and report no difference between the two study groups (RR 0.95 95% CI 0.69 to 1.35). Referring back to section 2.2.7.2.2 (the statistical analysis of falls), if the authors had only reported the time to first fall they would have erroneously concluded that the intervention was ineffective. The same research group conducted a second RCT examining the effect of expedited second-eye cataract surgery. Although this study demonstrated a similar rate reduction to the study of first eye cataract surgery (0.68 95% CI 0.39-1.19), the confidence interval included one [118]. The authors attributed their finding to the change in wait time status over the course of the study. The study was undertaken with an average 1 year wait for cataract surgery. Half way through the study the wait times improved to 6 months. The 46 investigators did not enrol sufficient number of participants to detect a difference in the rate of falls. Taken together these studies suggest that cataract surgery is likely successful in reducing the rate of falls. Australian falls researcher Bob Cumming extended the concept of a single-intervention for cataract surgery to a more comprehensive multidisciplinary vision assessment (new eye glasses, assessment with an occupational therapist, glaucoma management, and cataract surgery as appropriate) [119]. He and his colleagues randomised 616 men and women aged 70 years and older to receive comprehensive vision care or to usual care. In an apparent paradox, the intervention group was associated with an increased risk of falls (1.57,95% C11.20-2.05). This may have been due to the fact that the changes in prescription in the intervention group were major and that older frail individuals may need a substantial period of time to adjust to new eyeglasses and may be at increased risk during this time [119]. An interdisciplinary approach to falls prevention can include physiotherapists and occupational therapists undertaking environmental modifications. In their meta-analysis of RCTs of falls prevention, Chang and colleagues concluded that environmental modifications and education interventions were unlikely to be beneficial based on meta-analysis (5 studies, IRR 0.85 95% CI 0.65-1.11) [120]. However, both the Cochrane Review [8] and Kannus and colleagues' Lancet review [121] conclude that home hazard assessment and modification that is professionally prescribed for older people with a history of falling is effective is reducing the risk of falls. A recent RCT conducted by Campbell and colleagues supports this conclusion [122]. They enrolled 391 New Zealanders aged 75 years and older with severe visual impairment, and randomly allocated them to one of four groups: occupational therapy assessment and modifications, physiotherapist delivered home-based balance and strength retraining, both interventions, or neither intervention. Participants who received the home occupational therapy assessment and modifications significantly reduced their risk of falls compared to those who did not receive this intervention (IRR 0.59 95% CI 0.42-0.83)[122]. 2.2.8.2 Multifactorial interventions In addition to the largely unifactorial intervention summarized above, multifactorial interventions have proven successful in preventing falls. The rationale for this approach is that falls risk is the net result of various risk factors that are at least somewhat independent (i.e., vision, strength). Multifactorial intervention strategies may include strength/balance retraining (discussed in detail in the following section), home occupational therapy assessment, medication rationalization, management of postural hypotension and management of carotid sinus syndrome, as discussed individually above. A systematic review and meta-regression by Chang and colleagues included seven randomized controlled trials that aimed to prevent falls in older adults using a multifactorial intervention strategy [120]. They concluded there was good evidence to support multifactorial interventions (IRR 0.63 95% CI 0.49-0.83) [120]. This finding is substantiated by both the Cochrane Systematic Review of Falls Prevention Interventions (last substantial update on July 14,2003) [8] and a systematic review by Kannus and colleagues [121]. The Cochrane 47 Review included four trials that randomly allocated participants to multifactorial intervention or to usual care. The meta-analysis demonstrated that the intervention group was associated with 27% rate reduction (RR 0.73, 95%CI 0.63-0.85). The Cochrane Review also included five trials that enrolled persons selected because of known risk factors including history of a previous fall. The meta-analysis demonstrated a 14% rate reduction (RR 0.86,95% CI 0.76-0.98) [8]. Kannus and colleagues also concur with both of the previous reviews stating that multiple intervention strategies can prevent falls by 20-45% [121]. As the most recent systematic review was published in 2005 and preceded an important study by Lord and colleagues [86]. These Australian researchers enrolled 620 men and women aged 75 years and older and randomly allocated them to one of three groups: the extensive intervention group (EIG) that received individualized interventions comprising exercise and strategies for maximizing vision and sensation; the minimal intervention group (MIG) that received brief advice about falls prevention strategies; or, the control group (CG) that received no intervention [86]. Although the EIG group demonstrated significant improvements in knee extension strength, sit to stand times, and improved visual acuity and edge contrast sensitivity (in those who were eligible for the vision intervention) compared with CG, rate of falls was similar across all three groups. Compliance with the exercise intervention (a component of the EIG intervention) was poor (27%). The authors speculated that they may not have targeted a sufficiently at-risk group [86]. To avoid this risk my RCT (Chapter 4) was undertaken in those who had already fallen, and thus, were at 2-3 times the fall risk of a healthy community-dwelling person. 2.2.8.3 Physical activity A meta-analysis conducted by Chang and colleagues combined all RCTs of exercise interventions that measured falls, including both general exercise and those specifically targeting balance/strength/gait [120]. They addressed two outcomes: the proportion of participants who fell at least once and the monthly rate of falls. Among thirteen studies the results suggest that exercise significantly reduced the number of participants who fell at least once, (RR 0.86 95% CI 0.75-0.99). Among nineteen studies the results suggested that the monthly rate of falls was reduced to the same extent as the risk of having one fall, however the confidence interval included one (IRR 0.86 95% CI 0.73-1.01). To examine the effect of different types of exercise on falls, the authors estimated incidence rate ratio for monthly rate of falling. Five studies of endurance-type exercise were included, and these intervention were associated with an increased risk of falls (IRR 1.53 95% C11.04-2.25). This is an important and generally, under-appreciated finding. Balance- and strength- type exercise were associated with a decreased risk of falls, however the confidence intervals included one (IRR 0.78 95% CI 0.60-1.01 and 1.01 95% CI 0.76-1.42 respectively).To my knowledge, two meta-analyses of physical activity interventions to prevent falls include data at the individual participant level—the meta-48 analysis of a specific intervention of strength and balance retraining, called the Otago Exercise Program [123] and the pre-planned meta-analysis of the seven randomized controlled trials included in the Frailties and Injuries: Cooperative Studies of Intervention Techniques (FICSIT) [124]. I first outline details of the FICSIT meta-analysis and then the Otago Exercise Program is discussed in detail in the following section. The meta-analysis of the FICSIT trials included seven randomized controlled trials conducted in different centres across the United States [124]. These studies measured a common set of balance and strength measures. Two trials were conducted in nursing home settings and the remainder were in the community-dwelling population. All interventions included an exercise component including endurance exercise, platform balance, tai chi, and resistance training. The incidence rate ratio for the monthly rate of falling was 0.90,95% CI 0.81-0.99 for all groups who received any type of exercises compared to the control groups. A separate analysis was done for only those exercise interventions that included a balance component, and the results suggest a further 7% reduction in the rate of falls (IRR 0.83 95% CI 0.70-0.88). This meta-analysis provides evidence, at the individual level, that exercise can prevent falls and that exercise interventions with a balance training component may confer even greater benefit in preventing falls. The evidence provided by the meta-analyses reported by Chang and colleagues [120] and the FICSIT research group are supported by the Cochrane Systematic Review [8] and by a systematic review conducted by Kannus and colleagues [121]. These reviews both concluded that exercise is likely effective in preventing falls, particularly if the exercise has a balance training component. 2.2.8.3.1 The Otago Exercise Program Only one exercise protocol has been tested in over 1000 participants and the Cochrane systematic review specifically highlights the effectiveness of this program-- the Otago Exercise Program [8].The Otago Exercise Program (OEP) is a home-based progressive balance and strength retraining program initiated by a health care professional (a physiotherapist or nurse). The exercises consist of the following strengthening exercises: knee extensor (4 levels), knee flexor (4 levels), hip abductor (4 levels), ankle plantarflexors (2 levels) and ankle dorsiflexors (2 levels). The balance retraining exercises consisted of the following: knee bends (4 levels), backwards walking (2 levels), walking and turning around (2 levels), sideways walking (2 levels), tandem stance (2 levels), tandem walk (2 levels), one leg stand (3 levels), heel walking (2 levels), toe walking (2 levels), heel toe walking backwards (1 level), and sit to stand (4 levels). In addition to a website1 the details of the exercise program are also illustrated and detailed in a dedicated publication [125], A selection of exercises is prescribed at the first visit. Three additional home visits are scheduled every other week and the exercises are progressed as appropriate. A fifth "booster-visit" is scheduled at 6-months to make any necessary 1http://www.acc.co.nz/wcm001/idcplg?ldcSemce=SS_GET_PAGE&ssDocName=WCM002143&ssSourceNodeld=4249 49 changes to the exercises. The participant is expected to complete the exercises at least 3 times per week and walk at least 2 times per week [125] To date five randomised controlled trials have tested the OEP—three two-parallel groups RCTs [4,126,127] and two 2x2 factorial design RCTs [115,122]. Table 2.7 describes these studies in detail. All of these studies have been undertaken by the same research group from the University of Otago led by Professor John Campbell (Geriatric Medicine) and Associate Professor Clare Robertson (Epidemiology/Biostatistics). Three of the five OEP intervention studies demonstrated a significant reduction in the risk for future falls that ranged from IRRs in the OEP intervention group compared with control of 0.47 to 0.70 [4] [126,127]. Compliance --completing the OEP at least 3 times per week -- across the three successful studies was consistently 43% [4,126, 127]. Compliance for completing the program at least 2 times per week was 72% [126] and 62% [127]. It is noteworthy that the OEP demonstrated a persistent beneficial effect when continued over two years. Participants in an initial '12-month' study [4] were asked to either continue with their exercises on their own without further direction from the physiotherapist or to continue receiving usual care. In this RCT extension, there was no further input from the physiotherapists to deliver the OEP [128]. A recent meta-analysis of four OEP trials [4,115,126,127]; indicated that using subgroup analysis, the OEP was particularly effective in preventing falls in two sub-groups: 1) among persons aged 80 years and older with at least one fall in the previous year (54.0 falls prevented per 100 person years), and 2) persons with at least one fall in the previous year (44.3 falls prevented per 100 person year) [123]. It is important to address the two OEP studies that did not demonstrate a significant reduction in the risk of future falls. Both of these RCTs used a 2x2 factorial design. The first study examined the impact of the OEP program and psychotropic medication withdrawal [115]. The investigators and participants were blinded to placebo or study medication; however, as in all RCTs of physical activity, participants randomized to the exercise intervention were aware of that allocation. This study demonstrated that a scheduled withdrawal from psychotropic medications reduced falls risk compared with those who continued to take their psychotropic medication. However, there was no synergistic effect of the OEP and psychotropic medication withdrawal, nor was there an effect of the OEP alone (IRR0.87 95% CI 0.36-2.09) despite 68% of participants completing the OEP at least 3 times per week. I propose at least two reasons for the apparent lack of effectiveness of the OEP. Firstly, the sample of 93 participants may have been too small to detect differences of the OEP alone as the studies that have demonstrated a significant effect of the OEP have enrolled between 233 and 450 participants [4,126,127], A sample size needed to detect a reduction in proportion of persons experiencing at least one fall from 0.5 to 0.3 (a=0.05, (3=0.20) is approximately 220 people (110 per treatment arm). Secondly, the follow-up time may not have been long enough to observe sufficient 50 number of events in both groups. The average follow-up time per person in this study was 37 weeks whereas the follow-up time in the successful OEP studies that demonstrated a reduction in risk of falls was 52 weeks. The most recent study of the OEP was a 2x2 factorial trial of the Otago Exercise Program delivered by a physiotherapist and a home-safety intervention delivered by an occupational therapist [122]. Three hundred and ninety-one visually-impaired persons aged 75 years and older were enrolled in this study and were followed for 52 weeks. As mentioned in the paragraph above, the OEP did not demonstrate a reduction in the rate of falls compared to those not receiving the OEP (IRR 1.15 95% CI 0.82-1.61). The home-safety intervention, however, was effective in reducing falls by 41 % (0.59 95% CI 0.42-0.83). The authors' suggested that one reason for not demonstrating an effect of the OEP was due to poor compliance with the exercise program. Only 18% of the participants completed the program at 3 times per week or more and 36% completed the program at least 2 times per week or more [122]. This contrasts starkly with the previous studies which consistently demonstrated compliance of 43% for completing the OEP at least 3 times per week and between 62-72% completing the program at least 2 times per week. In a sensitivity analysis, those who adhered to the exercise prescription (at least 3 times per week), the OEP demonstrated a significant reduction in risk of falls compared with those who did not receive the OEP. The study authors suggested that this group of persons with visual impairments may have been more frail than those enrolled in previous studies. This suggests there may be a 'frailty boundary', and persons whose frailty is beyond a certain threshold may not benefit from strength and balance retraining. Arguing against such a 'boundary' are reports of 113-174% improvements in muscle strength among those living in a nursing home [82,129] and 37% by those recovering after hip fracture [69]. Thus, the specifics of exercise prescription in populations who are frail, and at high risk of falls, remains to be determined. 51 Table 2-7 Randomized controlled trials of the Otago Exercise Program Author Study Design and duration Population Intervention Control Outcome Measures Results Campbell 1997[4] New Zealand 12 months n=233 Women s 80 yrs Community-dwelling Registered with a general practice Otago Exercise Program (OEP) delivered 4 times over first two months by a physiotherapist OEP 3x/week Walking 3x/week Social visits (SV)- 4 times over first two months Falls- over 12 months (monthly calendars) Exercise compliance-monthly calendars Muscle strength- at 6 months (dominant knee extensor muscle, electronic dynamometer) balance measures- at 6 months (side by side, semi tandem, tandem, single leg stands; scored as 4-test balance scale 5x Chair stand test Falls- SV (152 fall/113.4 p-yrs) and OEP (88 falls/108.8 p-yrs); RR by negative binomial regression 0.47; 95% CI 0.04 - 0.90 Muscle strength- no difference Balance- mean change in balance improved by 4 test balance score in OEP vs. SV 0.42 (0.86) and -0.01 (0.80); difference (95% CI) 0.43 (0.21-0.65) 5x chair stand test- greater proportion in OEP vs SV improved (RR 1.41; 1.07 to 1.87) Change in Fear of falling- SV vs. OEP (-6.1 (12.2) v-2.5 (11.1)) OEP compliance: 42% (48/114) completing the OEP 3 or more times/week @ 1 yr Author Study Design and duration Population Intervention Control Outcome Measures Results Campbell 1999 [128] New Zealand Trial-12 months + 12 months n=213 Women > 80 yrs Community-dwelling Registered with a general practice Completed the first year of 1997 trial and agreed to be monitored for an additional year OEP 3x per week (self-directed) with telephone contact with physiotherapist for advice and to maintain motivations Usual Care Falls-12 months (monthly calendar) Exercise compliance-12 months (monthly calendar) Falls: year 2 - 68 falls/72.2 p-yrs in control group and 50 falls/58.3 p-yrs in OEP; overall falls (baseline to end yr 2) 220 falls/185.6 p-yrs in control group and 138 falls/167.1 p-yrs in OEP; relative rate (95% CI) after 2 yrs 0.69 (0.49-0.97) Characteristics of those continuing with study at yr 2: higher physical activity score at baseline and 1 yr; participants taking fewer medications at baseline; participants with higher falls efficacy at 1 year OEP compliance: 31/71 (44%) completed OEP at least 3x/week; those compliant at yr 2 more likely to report a fall in year prior to study; sustained higher falls efficacy score during 1st yr compared with all those randomized to the OEP group at baseline Campbell 1999 [115] New Zealand 2x2 factorial design 44 weeks n=93 17 general practices in Dunedin Women and men > 65 yrs Registered with a general practitioner Currently taking psychotropic medication 1. Gradual withdrawal of psychotropic medication: 80% of the original dose after 2 weeks, 60% after 5 weeks, 40% after 8 weeks, and 20% after 11 weeks, 0% after 14 weeks (double blind) 2. OEP: physiotherapist delivered, 4 visits over first 2 months; expected to complete 3x/week (single blind) 1. No psychotropi c medication withdrawal 2. No OEP Falls-12 months (monthly calendars) Falls: Average follow- up 37.7 weeks per person. Medication withdrawal group 17 falls vs. 40 falls original medication group; OEP group 22 falls vs. 35 falls no OEP group. RR for falls medication withdrawal group compared with group taking original medicine 0.34 (95% CI, 0.16- 0.74); risk of falling for the exercise program group compared with those not receiving the exercise program was not significantly reduced (0.87 95% CI 0.36-2.09) OEP compliance: at 44 weeks 20/32 (63%) were completing OEP at least 3x per week o n o o Author Study Design and duration Population Intervention Control Outcome Measures Results Robertson #1 2001 [126] New Zealand 1 year follow-up n=240 men and women > 75 yrs Otago Exercise Program (OEP) delivered 4 times over first two months and a booster visit at 6 months by a district nurse from community health center OEP 3x/week Walking 3x/week Usual care Falls: monthly falls calendar (12 months) OEP compliance: monthly calendar (12 months) Falls: control group had 109 falls/108.33 p-yrs and OEP had 80 falls/116.79 p-yrs; IRR 0.54, 95% CI 0.32-0.90); effective in those 80 yrs and older but not those 75-79 yrs OEP compliance: 49/113 (43%) completed OEP at least 3 times per week, 81/113 (72%) completed OEP at least 2 times per week Robertson #2 2001 [127] New Zealand 1 year followup n=450 men and womens 80 yrs Otago Exercise Program (OEP) delivered 4 times over first two months and a booster visit at 6 months by a practice nurse from general practice offices OEP 3x/week Walking 3x/week Usual Care Falls: monthly falls calendar (12 months) OEP compliance: monthly calendar (12 months) Falls: control group had 105 falls/111.83 p-yrs and OEP had 198 falls/291.7 p-yrs; IRR 0.70 95% CI 0.59-0.84); no difference between men and women OEP compliances 14/265 (43%) completed OEP at least 3 times per week; 164/265 (62%) completed OEP 2 times per week Campbell 2005 [122] New Zealand 2x2 factorial design 1 year follow-up n=391 men and women> 75 with visual acuity of 6/24 or worse community-dwelling 1. Otago Exercise Program (OEP) delivered 4 times over first two months and a booster visit at 6 months by a physiotherapist; OEP 3x/week; Walking 3x/week; plus vitamin D supplementation 2. Home safety assessment and modification programme by an occupational therapist No OEP No home safety assessment Social visits (to persons randomised to not receive either intervention) Falls: monthly falls calendar (12 months) OEP compliance: monthly calendar (12 months) Falls: HS + OEP 108 falls/92.24 p-yrs; HS alone 64 falls/98.12 p-yrs; OEP alone 120 falls/92.36 p-yrs; SV alone 151 falls/91.31 p-yrs; all HS 172 falls/190.36 p-yrs; No HS 271 falls/183.94 p-yrs; all OEP 228 falls/184.87 p-yrs; no OEP 215 falls/189.43 p-yrs. IRR HS vs no HS 0.59 (0.42 to 0.83); HS vs SV 0.39 (0.24 to 0.62); OEP vs no OEP 1.15 (0.82 to 1.61); OEP vs. SV 0.70 (0.48 to 1.28). OEP compliance: 3x/week 36/195 (18%); at keast 2x.weej70/195 (36%) OT compliance: 152/169 (90%) J i . 2.2.9 Clinical guidelines for falls prevention In this clinically-relevant area of research, it is pertinent to review the current status of Clinical Guidelines for falls prevent. Guidelines are important because they translate evidence from randomized controlled trials into recommendations for falls prevention in different setting (e.g., community-dwelling, long-terms care, in-hospital). Three sets of guidelines have been developed relating to falls prevention: the American Geriatrics Society/British Geriatrics Society/American Academy of Orthopedic Surgeons Panel on Falls Prevention (AGS/BGS/AAOS); the British Medical Association guideline development group (BMA); University of California Los Angeles Emergency Department guidelines (UCLA ED). Two of these (AGS/BGS/AAOS and BMA) pertain to the broad community-dwelling population [22,23] and the third (UCLA ED) specifically address persons presenting to the emergency department with a fall [130].These guidelines essentially recommend similar actions and intervention, and therefore I will discuss the most recent guideline for falls prevention, those developed by the AGS/BGS/AAOS [23].The AGS/BGS/AAOS fall prevention guidelines [23] address two groups: 1) healthy older persons presenting as part of routine care and 2) older persons presenting with one or more falls, or who have abnormalities of gait and/or balance, or who report recurrent falls. The guidelines recommended that primary care providers of healthy older persons ask patients about falls once per year. Patients who report a fall should perform the Timed Up and Go (TUG) test and those who demonstrate difficulties or abnormalities performing the TUG (i.e., >13 seconds) require "further assessment". The guidelines recommend that "further assessment: is a fall evaluation performed by a clinician with appropriate skills and experience, such as a geriatrician". A fall evaluation is an assessment that includes the following: a history of fall circumstances, medications, acute or chronic medical problems, and mobility levels; an examination of vision, gait and balance, and lower extremity joint function; an examination of basic neurological function, including mental status, muscle strength, lower extremity peripheral nerves, proprioception, reflexes, tests of cortical, extrapyramidal, and cerebellar function; and assessment of basic cardiovascular status including heart rate and rhythm, postural pulse and blood pressure and, if appropriate, heart rate and blood pressure responses to carotid sinus stimulation. Findings from this assessment may necessitate referrals to relevant specialists (e.g., cardiology, neurology) and interventions (e.g., multifactorial intervention, medication rationalization, strength and balance retraining). As discussed in section 2.2.4, a history of at least one fail is a strong predictor of subsequent falls, thus I focus on the portion of the guideline directed to these persons. To my knowledge, there has only been one study of whether clinicians implement guidelines for falls prevention in persons presenting to the emergency department due to a fall. This prospective cohort study was conducted by the Baraff and colleagues, the same researchers who developed the UCLA ED guidelines [131]. This study enrolled 1340 participants over a one year period at three emergency 55 departments that were part of a large Health Maintenance Organization (HMO) in southern California. During the two week period following pre-intervention enrolment period, the UCLA ED guideline was presented to the emergency department (ED) staffs, the internal medicine and family medicine primary care providers at the three participating EDs. During the post-intervention period, the implementation of the guideline was the responsibility of medical, nursing and clerical staffs at each ED. In the year following guideline dissemination, 759 participants were enrolled in the post-intervention period. Participants were contacted by telephone on the one-year anniversary of their fall and asked how many falls they had sustained a fall during the past 12 months. This study concluded that a two-week educational training session of ED staff was not successful in reducing the proportion of fallers (18% in pre-intervention vs 21% in the post-intervention). Although the rate of falls in each group was not statistically compared, both groups experienced a falls rate of 36.2 falls per 100 person-years. The authors state in their conclusion that the likely reasons for not demonstrating a reduction in the proportion of fallers was because there was no on-going quality management in the ED after guideline dissemination and that the ED staff reported that the limited time available for patient care in the ED made it difficult to comply with the guideline. The authors concluded that the intervention may have been more effective if potentially eligible patients were identified by review of the ED logs and if the guideline could be implemented and monitored by a geriatric nurse practitioner. They also suggested that the nurse practitioner could coordinate changes in health care as appropriate. Although outside the scope of this literature review, I note that a subsequent RCT of a nurse-led intervention for geriatric patients in the ED had beneficial health outcomes for all seniors (not only fallers) [132], The same year the UCLA ED guideline study was published, a UK randomized controlled trial called the Prevention of Falls in the Elderly Trial (PROFET) was published in the Lancet [2]. Three hundred and ninety-seven community-dwelling persons aged 70 years and older who presented to the emergency department with a fall were enrolled in the study. Participants were randomly allocated to a bidisciplinary assessment including comprehensive geriatric assessment with a single geriatrician, occupational therapy assessment and referral to relevant services if indicated, or to usual care. This study demonstrated two striking features. Firstly, after 12 months of follow-up the intervention group demonstrated a remarkable reduction in risk of falls (61 %) [2,133]; larger than any previously or currently demonstrated in the literature. Secondly, this study highlighted the suitability of the emergency department for identifying those who may be most at risk for future fall (50% of individuals in the control group sustained a fall as compared with 30% in the unselected community-dwelling population) [2] The evidence for the effectiveness of this particular intervention strategy was confirmed by Davison and colleagues in a 2005 study [3]. In this particular study, 313 persons aged 65 years and older who presented to the emergency departments of two UK hospitals with a fall and had sustained at least one additional fall in the previous year. Participants were randomly allocated to receive a structured medical, occupational therapy, and physical therapy assessments and interventions, or to usual care. This study demonstrated that the intervention reduced the rate of falls by 36% (IRR 0.64 95% CI 0.46-0.90), however the proportion of persons sustaining at least one fall was not significantly reduced; 65% in the intervention group and 56 68% in the usual care group. The findings from the PROFET study have been incorporated into the AGS/BGS/AAOS and the BMA guideline. The AGS/BGS/AAOS guideline is currently being updated (www.americangeriatrics.org). The findings from these two UK studies suggest that targeting persons who present with a fall- related injury to the emergency department using a structured intervention (comprehensive geriatric assessment, occupational therapy, physical therapy and targeted referrals) delivered outside of the emergency department setting can prevent falls. The assessment and interventions utilized in these studies are similar to the AGS/BGS/AAOS guideline recommendation for persons who fall and present to medical attention. 2.2.10 Gaps in current knowledge that motivated my thesis studies The AGS/BGS/AAOS guideline and evidence from randomized controlled trials [1,2] suggest that multifactorial intervention can prevent falls in older persons with a history of falls. However, it remains unknown what proportion of persons presenting to the emergency department with a fall receive care consistent with the published guideline. The medical literature contains many examples of 'gaps in care'—inconsistencies between what is recommended in clinical guidelines and what is delivered as 'usual care' [134-136] Evidence from three randomized controlled trials, an individual-level meta-analysis and the Cochrane review suggests that the Otago Exercise Program -- a home-based balance and strength retraining program initiated by a physiotherapist -- can prevent falls in older adults. Whether such a program is effective among seniors with a history of a previous fall remains unknown. The meta-analysis of four OEP randomized controlled trials suggested that falls can be prevented in persons with a history of a fall (compared to the control group). In contrast, falls increased among seniors who started strength and balance retraining in a nursing home [6]. It remains unknown if the Otago Exercise Program, delivered within a falls clinic that delivers care consistent with published guidelines (standard care), is effective in ameliorating risk factors for falls compared to standard care alone in community-dwelling older adults. While undertaking the literature review for the randomized controlled trial discussed above, I became aware that randomized controlled trials of falls prevention studies were not consistently utilizing statistical methods appropriate for the analysis of recurrent events. I therefore assessed the prevalence of RCTs that utilized statistical methods appropriate for recurrent events, and whether or not the use of these methods had improved over time. Additionally, while investigating recurrent events I was introduced to the Mean Cumulative Function. To my knowledge this method, had not been previously utilized in the falls literature. Therefore, I explored the use of the Mean Cumulative Function to compare falls events. To address these four gaps in the literature, I undertook four studies. The rationale, objectives, hypotheses and potential contribution of each of these studies is outlined in the following section. 57 2.3 Rationale, Objective and Hypotheses My thesis includes two clinical investigations and two methodological studies. Here I outline the rationale, objective, hypotheses and the potential contribution each study will make to the field for each of the four studies. 2.3.1 Study 1: Emergency department fall-related presentations do not trigger fall risk assessment: A gap in care of high-risk outpatient fallers Rationale: Older persons with a history of at least one fall in the previous year are at increased risk for future falls. A randomized controlled trial, published in 1999, of older persons presenting to the emergency department demonstrated that geriatrician assessment and appropriate referrals could prevent falls [2]. Results from this 1999 publication have been incorporated into falls prevention guidelines developed by the American Geriatrics Society/British Geriatrics Society/American Academy of Orthopedic Surgeons [23]. These guidelines suggest that persons who present to a health care provider after a fall should receive a comprehensive falls risk assessment followed by appropriate referrals and interventions. Anecdotal evidence from the emergency department at Vancouver Acute Hospital suggests that this was not the case as the focus of management is the acute problem-not the sequelae of the fall. Objective: The primary aim will be to determine whether women aged at least 70 years who present to the emergency department with a fall and are not admitted to the hospital receive referrals consistent with a published guideline- the American Geriatrics Society/British Geriatrics Society/ American Academy of Orthopedic Surgeons guideline. Potential contribution: This will be the first study to determine whether referrals consistent with a published guideline are reported by older women who present to the emergency department after a fall. If the study demonstrates a gap in care, it would provide evidence to develop and implement systems that would allow sustainable delivery of care consistent with guidelines to a population at high-risk of future falls and injuries. 58 2.3.2 Study 2: Action Seniors!: A randomised controlled trial of a home-based balance and strength retraining program Rationale: Falls in the elderly represent a significant health and economic burden in Canada and around the world. The Otago Exercise Program, a strength and balance training program for seniors, has demonstrated effectiveness (reduced rate of falls in the intervention group) in three randomized controlled trials. On the other hand, if older people undertake physical activity, it may increase their exposure to experience falls [6,137]. One randomized controlled trial, that included a strength and balance training component, among those living in a nursing home increased the rate of falls in the intervention group compared to the control group [6]. Thus, it remains unknown Whether strength and balance training is effective in ameliorating fall risk factor profile among community-dwelling seniors with a history of falls. Objective: The primary objective of this 6-month randomized controlled trial will be to examine the effect of the Otago Exercise Program on falls risk profile in persons with a history of falls requiring medical attention. The secondary objectives will includes evaluation of an effect of the Otago Exercise Program on rate of falls. Primary hypothesis: After adjusting for age, sex, referral route, and clinic physician, that there will be a 30% difference (baseline to 6-months) in fall risk profile as measure by the Physiological Profile Assessment between intervention and control group. Potential contribution: This will be the first randomised controlled trial of the Otago Exercise Program in persons who required fall-related medical attention and who had a comprehensive geriatric assessment in a falls clinic. Thus, the intervention examines 'secondary prevention' of falls. Results from this study will inform policy relating to physical activity prescription for high-risk seniors in a major urban centre. 59 2.3.3 Study 3: A systematic review of statistical methods reported in randomized controlled trials of falls prevention in older adults Rationale: Thirty percent of older persons fall once each year and half of those individuals experience falls recurrently. A review of the falls prevention literature revealed inconsistent use of statistical methods appropriate for recurrent events. Use of inappropriate statistical methods may result in the incorrect study conclusion (Type I and Type II errors). Objective: The primary objective of this study will be to systematically review the use of appropriate statistical methods for recurrent events in falls prevention randomized controlled trials and to compare the proportion of studies using such methods across two time periods. Potential contribution: This will be the first systematic review to describe the statistical methods used for reporting recurrent events in the falls literature. If the reporting of falls proves to be suboptimal, the study will provide recommendations for improving standards for reporting recurrent events. 60 2.3.4 Study 4: The utility of the Mean Cumulative Function in detecting differences between groups experiencing different intensities of fall events Rationale: Falls are the most common cause of injury among elderly people and half of those who fall do so recurrently. Methods that analyze only the first event ignore the potential impact of interventions on subsequent events. Poisson regression is a method that incorporates all events but assumes that the events within participants are independent, which may not be the case. There are several methods available to analyze recurrent events, where the events may be dependent, such as the Andersen-Gill regression model, the marginal model (Wei Lin and Weissfeld), and negative binomial regression [138,139], These methods calculate the average rate of events in the study population. The Mean Cumulative Function (MCF) is another statistical method appropriate for analyzing recurrent events. It describes the average number of events occurring in one individual within a certain time [140, 141] and this has not previously been used to analyze multiple events in falls research [141]. Objective: To utilize simulations to explore the use of the mean cumulative function to compare fall events between groups. Primary hypothesis: I hypothesise that the MCF will be able to detect differences between groups experiencing different patterns of event intensities, defined as the number of events per unit of time, (the shorter the time between events, the greater the intensity). Potential contribution: This will be the first study to evaluate the utility of Mean Cumulative Function using data simulated on an intervention program, home-based balance and strength retraining, known to reduce the risk of falls. Results from this study will help to guide future analyses of falls intervention studies. The MCF may provide an additional statistical method by comparing groups using 95% confidence intervals and complement regression models developed for recurrent event analysis. 61 2.4 References 1. Tinetti, M.E., et al., A multifactorial intervention to reduce the risk of falling among elderly people living in the community. The New England Journal of Medicine, 1994.331(13): p. 821-827. 2. 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Rodriguez. 2003, Philadelphia: SIAM. 151. 3 Study 1: Emergency department fall-related presentations do not trigger guideline assessment: A gap in care of high-risk outpatient fallers2 3.1 Introduction The emergency department is a frequent point of contact with the health care system after a fall because of the associated incidence of serious injury, including fracture [1], People who have fallen (hereafter referred to as "fallers") and present to the emergency department with fall-related injuries are at high risk of recurrent falls [2].The Prevention of Falls in the Elderly Trial (PROFET) study, a randomized controlled trial, demonstrated that geriatrician assessment and appropriate referral significantly reduced subsequent falls in this population [2]. Moreover, there was a two-fold reduction in the proportion of persons sustaining a fracture [2].The results from the PROFET study have been incorporated into two guidelines developed by the American Geriatrics Society/British Geriatrics Society/American Academy of Orthopaedic Surgeons (AGS/BGS/AAOS) [3] and by the British Medical Association guidelines development group [4]. Briefly, the AGS/BGS/AAOS recommend a person sustaining injury after a fall should have a fall evaluation performed by a person with appropriate skills and experience, such as a geriatrician [3]. A fall evaluation is a clinical assessment that includes: a history of fall circumstances, medications, acute or chronic medical problems, and mobility levels; an examination of vision, gait and balance, and lower extremity joint function; an examination of basic neurological function, including mental status, muscle strength, lower extremity peripheral nerves, proprioception, reflexes, tests of cortical, extrapyramidal, and cerebellar function; and assessment of basic cardiovascular status including heart rate and rhythm, postural pulse and blood pressure and, if appropriate, heart rate and blood pressure responses to carotid sinus stimulation [3]. Geriatrician-researcher Professor Mary Tinetti, the principal investigator of the first successful multifactorial intervention to prevent falls in community-dwelling older adults, [5], noted that delivery of falls care is a problem. She contended that "...there is no simple mechanism in our fragmented, disease-oriented healthcare system for referring individuals to the relevant professionals..." [6]. Anecdotal evidence from emergency department physicians at Vancouver Acute Hospital suggested that this may also be the case locally because medical focus is directed towards acute management of the fall. Follow-up with the family physician and referrals may need to focus on a variety of medical sequelae, but not falls per se. I documented the care of women, aged at least 70 years, who presented to the emergency department with a fall and were not admitted to the hospital. The majority of persons presenting to the emergency department with falls are 2 A version of this chapter has been published. Donaldson MG, Khan KM, Davis JC, Salter AE, Buchanan J, McKnight D, Janssen PA, Bell M, McKay HA. Emergency Department fall-related presentations do not trigger fall risk assessment: a gap in care of high risk out-patient fallers. Arch Gerontol Geriatr. 2005 Nov-Dec;41(3):311-7. 71 women [2]. My aim was to determine whether this population received care consistent with AGS/BGS/AAOS guidelines. 3.2 Methods I conducted a survey of women aged 70 years and older reporting to the emergency department due to a fall (index fall) at the Vancouver Hospital Emergency Department (ED) during the period August 1, 2001 to May 1 2002. The Vancouver Hospital is the largest academic hospital in British Columbia, Canada and the ED is a provincial trauma referral centre with approximately 56,000 visits per year. Ethical approval for the study was obtained from the Clinical Research Ethics Boards of the University of British Columbia and Vancouver Acute Hospital. Women were eligible if they were at least 70 years of age, were community-dwelling, presented to the ED with a fall related injury, and were not admitted to the hospital. Eligible participants were identified by reviewing the ED census (MD, JB). This 24-hr record of patients documents the age of the patient, the mode of arrival (ambulance, self, air ambulance) and the nature of the complaint documented at triage. Complete ED records of patients presenting with an injury that could be the result of a fall were reviewed to confirm the nature of the injury and the specific details of the injury. After confirming eligibility from the ED patient records, eligible women were sent an initial letter of contact approximately 18 months after their ED presentation. The letter invited them to participate in a telephone interview regarding their fall. This letter outlined three dates and times that I would attempt to contact them. Upon telephone contact, women were asked if they received the letter, if they had any questions about the survey, and if they were interested in participating. If so, verbal consent was obtained. The 45-minute structured interview, based on the AGS/BGS/AAOS fall evaluation assessment, asked women about: referrals received after the index fall (family physician, falls clinic, footwear assessment, home hazard assessment, bone density scanning, orthopaedics, physiotherapy, vision assessment, advice on hip protectors), medication use (including bisphosphonates, calcium and vitamin D), living arrangements and falls history (living arrangements pre and post ED presentation, falls pre and post ED presentation, fracture history, history of osteoporosis, history of bone density assessment) and finally questions relating to vision (use of prescription lenses, last date of eye exam, history of cataracts). A fall was defined as unintentionally coming to rest on the ground or other lower level, not caused by overwhelming external force [7]. My primary outcome of interest was the proportion of women who reported each type of referral, as indicated by the AGS/BGS/AAOS guideline. 72 3.3 Results Two hundred and twenty six fall-related emergency department records were assessed for eligibility. Among these, 45 women were excluded due to hospitalization for hip fracture and 181 participants were sent a letter of invitation for the study. Of these, 28 women were no longer alive (15%) and 20 (11%) women declared residence in a care facility prior to the index fall. I enrolled 47% (63/133) of the eligible women (Figure 3.1). Fifty-three percent (70/133) declined participation and of these, 10 were due to illness. The mean age of participants was 81.2 + 6.2 years. Forty-four percent of participants reported falling at least once during the 18-month period between the index fall and participating in the telephone survey. The most frequent referral was to the family physician, 32% (20/63) 95% confidence interval 21-43%, followed by referral to physiotherapy 24% (15/63), 95% confidence interval 14-34% (Figure 3.2). Only one woman reported being referred to a falls clinic. After presenting to the emergency department, two women reported being referred for bone densitometry. Thirty-three percent (21/63) of women had previously had their bone density measured. None of the participants reported a referral for vision assessment even though 91 % of the women wore prescription glasses. Forty-nine percent of the participants reported having their eyes examined within the last year and 81% had had their eyes examined in the previous two years. In the 18-months post ED fall three women who previously lived alone moved in with family members, two women who previously lived alone received homecare and one woman who previously lived with family moved to a retirement home. This 10% (6/63) of participants, over an 18-month period, required a more supportive living arrangement after a fall. 3.4 Discussion I report that only 32% of older women who presented to the emergency department with a fall-related injury and were not admitted reported having been referred to their family physician. These findings suggest that the results of the PROFET intervention study [2], published in 1999, have not yet been translated to clinical care. I note that although the emergency department routinely sends a copy of the patient record to the individual's family physician, this did not consistently prompt follow-up with the family physician for a fall evaluation assessment. Further, only 24% of women reported having been referred to physiotherapy. Few referrals occurred despite evidence from randomized controlled trials by Tinetti and colleagues [5] and Close and colleagues [2] that multifactorial intervention, including physiotherapy referral for balance and strength training, reduces falls. 73 The retrospective nature of this study limits the conclusions I can draw as patient self-report at 18-months may underestimate physician intervention to prevent falls. On the other hand, Cummings' [8] found that retrospective recall under-estimates the subsequent fall rate. I also note that despite the increasing attention being paid to diagnosing osteoporosis, only two participants were investigated for osteoporosis. Age is a major risk factor for osteoporotic fracture according to the Canadian Osteoporosis Guidelines [9] and recent evidence from the UK suggests that this would be an appropriate investigation in fallers as those with two or more risk factors for falls have lower bone mineral density compared to those with zero or one risk factor [10]. In summary, the majority of older women who presented to the emergency department with a fall did not report receiving AGS/BGS/AAOS guideline care. Strategies are required to provide an additional or alternative pathway to deliver guideline care to this group at high risk of further falls. Primary care physicians have the responsibility to follow-up patients who have had a fall requiring ED care. With appropriate dedicated time and training, the primary care provider could assess risk factors for further falls. I propose that future research use a prospective study design to assess whether or not care consistent with published guidelines is being delivered by a variety of health care providers after patients leave the Emergency Department and avoid the problem of recall bias. This study would also provide an opportunity to assess change in risk factors for falls, such as strength and balance, and to assess the occurrence of subsequent falls associated with referrals according to guidelines. Strategies to improve knowledge translation, such as continuing education in falls risk assessment for a multidisciplinary health care audience including geriatricians, physiotherapists, community health nurses, emergency physicians and primary care physicians is indicated to improve compliance with evidence-based guidelines. 74 Figure 3-1 Eligible participants for telephone survey of fall follow-up care 226 ED fall-related visits (August 1st 2001 and May 1st 2002) 181 letters of initial contact sent 133 women eligible 63 participants 45 excluded hospitalization due to hip fracture 28 deceased 20 residing in care facility at time of index fall (excluded) 60 refused 10 "too ill" 75 Table 3-1 Injuries sustained by 226 women presenting to the ED with a fall All women seen in ED Participants with a fall related injury (n=63) (n=226) Number (%) Number (%) hip fracture 45 (20) non-hip fracture 62 (27) 23 (37) laceration/bruise 28(12) 10(16) syncope and collapse 24(11) 5(8) sprain/strain/dislocation 11(5) 6(10) other 56 (25) 19(30) Table 3-2 The percentage of women (n=63) receiving referral, assessment or having a specific condition for: 'guideline care' for falls • ; bone health • ; and ophthalmological health 77 3.5 References 1. Bell, A , J. Talbot-Stern, and A. Hennessy, Characteristics and outcomes of older patients presenting to the emergency department after a fall: a restrospective analysis. Medical Journal of Australia, 2000.173: p. 179-182. 2. Close, J , et al. Prevention of falls in the elderly trial (PROFET): a randomized controlled trial. Lancet, 1999. 353: p. 93-97. 3. American Geriatrics Society, G.S, American Academy of, Orthopaedic Surgeons Panel on Falls Prevention, Guideline for the prevention of falls in older persons. Journal of the American Geriatrics Society, 2001.49: p. 664-672. 4. Feder, G , et al. Guidelines for the prevention of falls in people over 65. British Medical Journal, 2000. 321: p. 1007-1011. 5. Tinetti, M.E, et al , A multifactorial intervention to reduce the risk of falling among elderly people living in the community. The New England Journal of Medicine, 1994. 331(13): p. 821-827. 6. Tinetti, M, Where is the vision for fall prevention? Journal of the American Geriatrics Society, 2001.49: p. 676-677. 7. Kellogg International Work Group, The prevention of falls in later life. A report of the Kellogg International Work Group on the Prevention of Falls in the Elderly. Dan Med Bull, 1987. 34 Suppl 4: p. 1-24. 8. Cummings, S , M. Nevitt, and S. Kidd, Forgetting falls: The limited accuracy of recall of falls in the elderly. Journal of the American Geriatrics Society, 1988. 36: p, 613-616. 9. Brown, J.P. and R.G. Josse, 2002 clinical practice guidelines for the diagnosis and management of osteoporosis in Canada. Cmaj, 2002.167(10 Suppl): p. S1-34. 10. Newton, J.L, et al , A prospective evaluation of bone mineral density measurement in females who have fallen. Age Ageing, 2003. 32(5): p. 497-502. 78 4 Study 2: Action Seniors!: A randomized controlled trial of a home based balance and strength retraining program on risk factors for falls in older men and women who present to a falls clinic after sustaining a fall requiring medical attention 4.1 Introduction Falls and injuries resulting from falls in the elderly represent a significant health and economic burden in Canada and around the world [1-3]. Cohort studies have consistently demonstrated that 30% of those aged 65 years and older experience at least one fall each year and half of those fall recurrently [4-7]. Risk factors for falls include poor balance [4-7], impaired strength [4-7] and impaired reaction time [7]. To address risk factors that may be amendable, New Zealand researchers designed a physiotherapist-initiated, progressive home-based strength and balance training program [8-12], This intervention - The Otago Exercise Program - has demonstrated benefit in 4 studies of unselected community-dwelling seniors, defined as persons selected for inclusion based on aged alone. [8-12]. The Otago Exercise Program is also cost-effective in persons aged 80 years and older [11]. The Cochrane Collaboration specifically identifies the Otago Exercise Program (OEP) as the strength and balance training program with strongest evidence for effectiveness based on four randomized controlled trials [13]. These studies all qualified as exercise for primary prevention - the exercise was not part of a medical management plan for those who had fallen. In 2005, the OEP was tested in a novel cohort at risk for falls, men and women aged 75 year and older, who had severe visual impairment, defined as visual acuity of 6/24 or worse in the better eye after the best possible correction [14]. The OEP did not significantly reduce the rate of falls in the intervention group (incidence rate ratio 1.15 (0.82 to 1.61). The authors postulated that this was due to low adherence (18%) possibly due to the frail nature of the participants [14]. Although previous OEP RCTs included community-dwelling seniors who had had falls, it had not been specifically tested in seniors with a history of falls who were attending a dedicated clinic that included comprehensive geriatric assessment. Therefore, the primary objective of this randomized controlled trial was to study the effect of the Otago Exercise Program, delivered as a facilitated and mandatory component, on change in falls risk profile (PPA z-score) in participants who attended a falls clinic. I hypothesized that, from baseline to 6-months, the falls risk profile in participants randomized to receive the Otago Exercise Program ejus standard of care at the falls clinic would remain stable, whereas in those who received only standard of care alone at the falls clinic, the Physiological Profile Assessment score would worsen. This would lead to a net lower (i.e., less fall risk) Physiological Profile Assessment score in those randomized to the Otago Exercise Program plus standard of care 79 My secondary objectives were to explore the effect of the Otago Exercise Program on change in sub-components of the falls risk score, clinical performance measures, balance confidence and on the occurrence of falls. In addition I planned to report the change in patient behaviour at 6-months associated with recommendations from the falls clinic. I hypothesized that the change in two subcomponents of the PPA, knee extension strength and sway on a compliant surface with eyes open; as well as the timed up and go test would improve from baseline to 6-months in the intervention group. I also hypothesized that the incidence of falls would be lower in the intervention group over a 12-month period of observation. 4.2 Methods Participants were enrolled over a 19-month period beginning July 2004 from two dedicated referral-based falls clinics in Vancouver, British Columbia. The geriatricians who staffed the falls clinic accepted GP referrals of patients aged 70 years or older who had fallen and were considered at risk of further falls. Patients who attended the falls clinic received falls risk factor assessment followed by a comprehensive geriatric assessment. The falls clinic care pathway was based on the American Geriatrics Society/British Geriatrics Society/American Academy of Orthopaedic Surgeons Falls Prevention Guidelines [15] (which is hereafter referred to as "standard of care"). Specifically, falls risk factor assessment included the Physiological Profile Assessment (described in detail below) [16], performance measures (Timed Up and Go [17], one-time chair stand, five-time chair stand, gait speed, side by side stance, tandem stance, semi-tandem stance, single leg stance [18]), Mini Mental State Exam (MMSE) [19], Barthel Index [20] and Geriatric Depression Scale [21] were assessed in the falls follow-up clinic by a blinded assessor at baseline and at 6-month follow-up. Falls risk factor profile by PPA (see below) and the comprehensive geriatric assessment were completed at baseline and 6-months. Community-dwelling men and women aged 70 years and older were eligible to participate if they attended either of the dedicated falls clinics. Participants needed to be able to walk at least 3 meters because the Otago Exercise Program has a walking component. Participants also needed to meet one of the following criteria: a) one additional non-syncopal fall in the previous year to enrol participants whose index fall was suspected clinically to be due to carotid sinus syndrome; b) a Timed-Up and Go test time of greater than 15 seconds because this threshold has been associated with increased risk for falls [22] or a Physiological Profile Assessment (PPA) z-score of s 1 to enrol participants who were at risk for falls because this tool can discriminate between multiple and non-multiple fallers [7]. Participants were excluded if they had (a) Parkinson's disease — a progressive neurological condition, (b) life expectancy of <12 months as determined by the falls clinic geriatric medicine physician, or (c) cognitive impairment as measured by a Mini Mental State Examination < 24 [19]). 80 After confirming eligibility from the falls clinic records, eligible men and women were sent an initial letter of contact. The letter outlined the objectives of the study and outlined three dates and times that I would attempt to contact them. Upon telephone contact, men and women were asked if they received the letter, if they had any questions about the study, and if they were interested in participating. If the person agreed to participate further, I made an appointment to visit the participant at his/her home. At this visit the participant had the opportunity to ask any additional questions about the study and then gave written informed consent. I called the remote randomization centre to provide information regarding the three strata (sex, falls clinic referral route, falls clinic physician). I was informed of the participant's treatment assignment and I communicated this to the patient. The study was approved -by the Clinical Research and Ethics Board at the University of British Columbia, Vancouver Coastal Health Research Institute and the British Columbia Women's Hospital. All participants gave written informed consent. 4.2.1 Randomisation—allocation concealment The randomization sequence was computer generated (www.randomization.com) and consisted of 3 strata (sex, whether index fall had necessitated and emergency department visit or not, and falls clinic physician) and blocks of 6 participants. This sequence was held independently and remotely by the Family Practice Research Coordinator at the University of British Columbia. 4.2.2 Outcomes and covariates The Physiological Profile Assessment (PPA) was selected as the primary outcome because prospective studies have demonstrated it to be valid and reliable [7]. The PPA can accurately discriminate between multiple fallers (2 or more falls) and non-multiple fallers 74% of the time [7]. The PPA uses a Web-based software program to compare participants' performance to a normative database established from population cohort studies [7,23]. The PPA program generates a fall risk assessment report including the participant's overall falls risk score and the participant's performance on the five tests that comprise the PPA. A PPA z-score of 0-1 indicates mild risk, 1-2 indicates moderate risk, 2-3 indicates high risk, and 3 and above indicates marked risk [7,16, 24]. The five components of the PPA are edge contrast sensitivity, hand reaction time, lower limb proprioception, knee extension strength and sway [16]. Edge-contrast sensitivity was assessed using the Melbourne Edge Test [16]. Simple hand reaction time was assessed in milliseconds with participants seated using a finger press. Participants had 10 practice trials and 10 test trials. The average of the 10 test trials was the test score [16]. Proprioception was measured using a lower limb matching task with eyes closed. A vertical clear acrylic sheet (60 cm x 60 cm x 1cm) inscribed with a protractor was place between the participant's knees. Errors were recorded to the nearest degree. Participants had two practice trials and 5 test trials. The average of the 5 test trials was the test score [16]. Voluntary maximal knee extension 81 strength was measured using a dynamometer in a seated position of the dominant leg. Participants had one practice trial and 3 test trials. The best of the three test trials was the test score [16]. Postural sway was measured using a sway meter to measure displacement of the body at waist level. Participants performed sway assessment on firm and compliant (60 cm x 60 cm x 15 cm thick foam rubber mat) with eyes open and closed for 30 seconds) surfaces [16]. To complete the timed up and go test (TUG), the participant rises from a chair, walks 3 meters, turns 360 degrees, walk backs to the chair and returns to the seated position. A TUG cut-off level of at least 13.5 seconds correctly classified participants as fallers in 90% of cases [25]. A researcher administered the Physical Activity Scale for the Elderly (PASE) [26, 27] in the participant's home at baseline after the participant provided informed consent. The PASE is used to measure physical activity specific to older persons through a structured 7-day recall questionnaire. This measure was repeated at 6-months via telephone by a blinded assessor. This was a measure to ensure that the two groups were comparable at baseline. Geriatricians' baseline and 6-month Falls Clinic consult letter were photocopied and all patient identifiers were removed. Two researchers (KMK, physician; MGD, PhD epidemiology candidate), blinded to treatment allocation, abstracted relevant medical history [28, 29] and current medication and supplement use [28-31] from both the baseline and the 6-month consult letters. They also abstracted risk factors for falls and fractures identified at baseline [15], targeted interventions recommended at baseline and the uptake of these interventions as documented in the 6-month consultation. The Charlson comorbidity index [32] was calculated to estimate the cumulative increased likelihood of one-year mortality; the higher the score, the more severe the burden of comorbidity. The Functional Comorbidity Index was calculated to estimate the degree of comorbidity associated with physical functioning [33]. Both were calculated at baseline. Differences between abstractors were resolved by consensus or, where necessary, by a third party (WLC, geriatrician). 4.2.2.1 Ascertainment of falls and adherence to the Otago Exercise Program Ascertainment of falls and adherence (defined as the number of OEP days completed divided by the number of OEP days prescribed) to the Otago Exercise Program were documented on monthly calendars which were returned in pre-paid pre-addressed envelopes at the end of each month. Falls were defined as "unintentionally coming to the ground or some lower level and other than as a consequence of sustaining a violent blow, loss of consciousness, sudden onset of paralysis as in stroke or an epileptic seizure'" [34]. A research assistant, who was not blinded to treatment group, but was unaware of the study hypotheses, made three attempts by telephone to contact participants at the end of each month. The purpose of each phone call was to inquire about falls and exercise adherence (OEP group 82 only) for all participants regardless of whether or not the calendar was returned. The research assistant also encouraged those in the Otago Exercise group to perform their exercises three times per week. The primary study outcome was the change from baseline to 6 months in the Physiological Profile Assessment z-score. The secondary outcomes were the change from baseline to 6 months in knee extension strength, sway on a compliant surface with eyes open, timed up and go test time and the incidence of falls. 4.2.3 Sample Size The sample size required, based on reducing the proportion of fallers in the OEP plus standard of care in the falls clinic group compared with standard of care in the falls clinic alone respectively, from 0.5 to 0.3 was 220 participants (110 per study arm) assuming 6=0.2, a= 0.05 and 15% attrition. A previous randomized controlled trial of multifactorial intervention conducted in the emergency department demonstrated that 50% of the control group fell at least once over the one year study period [29], After prospectively enrolling participants for 12 months, only 50 participants had been enrolled. After discussion with my committee it was decided to change the primary endpoint from falls to falls risk score as measured by the PPA. Based on previous prospective data from our emergency department cohort study [35], I assumed a baseline PPA score of 1.73 in both groups, I assumed that the PPA score in the standard of care delivered in the falls clinic group would increase by 0.51 units with a standard deviation of 0.9 units. I assumed that the baseline PPA score would remain unchanged in the Otago Exercise plus standard of care group over a 6 month period, with a standard deviation of 0.9 units. Assuming 6=0.2, a= 0.05 and 15% attrition I estimated a required sample size of 60 participants (30 per study arm). 4.2.4 Intervention- Otago Exercise Program The Otago Exercise Program (OEP) is a home-based balance and strength retraining program [9,36]. The exercises consisted of the following strengthening exercises: knee extensor (4 levels), knee flexor (4 levels), hip abductor (4 levels), ankle plantarflexors (2 levels) and ankle dorsiflexors (2 levels). The balance retraining exercises consisted of the following: knee bends (4 levels), backwards walking (2 levels), walking and turning around (2 levels), sideways walking (2 levels), tandem stance (2 levels), tandem walk (2 levels), one leg stand (3 levels), heel walking (2 levels), toe walking (2 levels), heel toe walking backwards (1 level), and sit to stand (4 levels). In addition to a website (URL) the details of the exercise program are also illustrated and detailed in a dedicated publication [36]. 83 The two physiotherapists who delivered the OEP had 27 and 16 years of clinical experience with older persons. For each patient randomized to the OEP, one of the physiotherapists visited the home and prescribed a selection of exercises at the first visit. The same physiotherapist returned biweekly 3 additional times to make progressive adjustments to the exercise protocol according to the OEP exercise manual. Each of these 4 visits in the first 2 months took approximately 1hour. The participant was encouraged to perform her/his exercise program 3 times per week (approximately 30 minutes) and to walk at least twice per week. Each participant was given an exercise manual with a picture and description of each exercise and an ankle cuff weight that could be adjusted in 0.9 kg increments, from 0.9 kg to 9 kg. The physiotherapist also visited the participant's home one final (5th) time 6 months after the initial visit to check that the program was being done correctly and to encourage the participant to persist. 4.2.5 Blinding This was a single-blind (assessor) study. Research assistants who administered the fall risk assessments, conducted the monthly telephone interview, and the post-fall telephone interview were all blinded to group assignment. The post-fall telephone interview was initiated by the research assistant after reviewing the monthly calendars; however, participants were instructed to call if they had a fall. As this was an exercise intervention, the participants and those administering the intervention (two physiotherapists) were aware of group assignment. 4.2.6 Statistical Analysis 4.2.6.1 Primary Analysis I used linear regression to model the relationship between average change in PPA z-score between OEP plus standard of care and standard of care alone adjusted for baseline PPA z-score. Variables entered into the model to obtain adjusted effects were decided a priori and included age, sex, referral route and falls clinic physician. By fitting this model, I obtained a regression coefficient for each variable. Regression estimates for the OEP plus standard of care group is the difference between study groups in average change in PPA z-score. The F-test was used to assess the significance of the association fitted by the model. Significance of the estimates was tested by individual t-tests. Results were considered significant at p<0.05. 84 4.2.6.2 Secondary Analysis I used linear regression, as described in the primary analysis, to model the relationship between average change in, knee extension strength, sway on compliant surface with eyes open and timed up and go time between OEP plus standard of care and standard of care alone adjusted for corresponding baseline score. Age, sex, referral route and physician variables are entered into the model to obtain adjusted effects. I compared the incidence of falls over a 12 month observation period between OEP plus standard of care and standard of care alone using negative binomial regression and the 95% confidence interval for the incidence rate ratio. I compared the mean number of falls per person by 12 months in both groups using the Mean Cumulative Function, the Mean Cumulative Function difference and their respective 95% confidence intervals [37-39]. 4.3 Results 4.3.1 Participant flow The recruitment process is shown in Figure 1.1 enrolled 74 participants over 19 months, representing 41% (74/179) of those eligible for the study. The mean age of the participants was 82.5 (SD 6.4) and ranged from 71-97 years. Over 60% (47/74) of the participants were at least 80 years old, and 72% (53/74) of the participants were women. I measured a number of demographic and clinical characteristics at baseline. Overall, the two groups were balanced at baseline, with the exception of the proportion of participants over the age of 80 (69% (25/36) OEP vs. 58% (22/38) SC). Baseline demographic and clinical characteristics and Physiological Profile Assessments scores are shown in Table 4.1. 4.3.2 Drop outs Eight participants dropped out of the study prior to the 6 month follow-up assessment; none dropped out after that time. Several participants were unable to make the final clinical assessment but all participants completed the falls diaries. The reasons for dropping out are detailed in Figure 1. Participants who did not return for 6 month follow-up were older than those who completed (85 years compared with 82 years), demonstrated increased overall Physiological Profile Assessment z-score (3.2 vs. 2.2) and demonstrated decreased balance (increased sway on foam). 85 4.3.3 Outcomes I enrolled 74 participants, 36 participants in the Otago Exercise Program plus standard of care group (OEP) and 38 in the standard of care group (SC). Thirty-four participants (94%) in the OEP group and 32 (84%) participants in the SC group returned for 6-month assessments. All participants provided at least one day of follow-up for the occurrence of falls. All analyses were "full analysis set" [40] (defined as the analysis set which is as complete as possible and as close as possible to the intention-to-treat ideal of including all randomized subjects). The falls incidence data were analyzed according to "intention to treat" [41]. The baseline and 6-month Physiological Profile Assessment score are shown in Table 4.2. Table 4.3 shows the regression estimate for the Otago Exercise Program adjusted for baseline PPA score. The change in PPA score was not associated with the Otago Exercise Program as measured by the t-test. The change in PPA z-score for participants in the Otago Exercise Program compared with those in the standard of care group, increased (improved) by 0.13 (95% CI, -0.32 to 0.58) (Table 4.2). The change in PPA z-score adjusted for age, sex, referral route and falls clinic physician was not statistically significant (0.10, 95% confidence interval -0.33 and 0.53) (Table 4-3). Both groups had a high proportion of participants who did not change from baseline to 6 months (Figure 4.2). The change in knee extension strength, sway and TUG was not associated with the Otago Exercise Program. The results of the linear regression models are summarized in Tables 4.3 and 4.4. Fifty-five percent of the standard of care group fell at least once and 35% of the OEP group fell at least once (Table 4-5). Using negative binomial regression and an intention to treat analysis, the unadjusted incidence rate ratio of falls in the OEP group, compared with the SC group was 0.46 (95% confidence interval 0.20 to 1.10). Intention to treat analysis of the incidence rate ratio of falls adjusted for sex, falls clinic physician, referral route, age and number of self-reported falls in the previous year was 0.62 (95% confidence interval 0.3 to 1.4). I removed three outliers in the analysis of falls. The three participants had experienced at least 18 falls each over the period of observation: one patient had high suspicion of carotid sinus syndrome as indicated in their 6-month falls clinic chart, one patient had frontal lobe gait ataxia, one patient had severe residual effects from a previous stroke that resulted in right foot scuffing. With these cases removed, the unadjusted incidence rate ratio of falls in the OEP group, compared with the SC group was 0.48 (95% confidence interval 0.2 to 1.0). The adjusted incidence rate ratio was 0.44 (95% confidence interval 0.23 to 0.84). Intention to treat analysis of the average number of falls per person, as measured by the Mean Cumulative Function, by 12 months was 1.2 and 2.8 in the OEP group and standard of care group respectively. The 95% confidence intervals for the two groups overlapped (Figure 4.3). On average there was one fewer fall in the OEP group compared with the standard of care group by 200 days, however the 95% confidence intervals always encompassed 86 zero (Figure 4.4). With three cases removed (as discussed above), the average number of falls per person was 0.7 and 1.4 in the OEP and SC groups respectively (Figure 4.5). On average there was 0.75 (95% CI 0.1 to 1.5) fewer falls in the OEP group compared to the standard of care group, as measured by the Mean Cumulative Function difference (Figure 4.6). The recommendations most frequently prescribed by the geriatricians at the patients' first appointments were vitamin D (52%, 31/59) and exercise for balance and gait impairments (34%, 21/59) (Table 4.6). At the 6-month follow-up visit, the uptake of interventions, was best for exercise (70%, 28/40). I note that 85% (17/20) of those who took up this recommendation were in the OEP intervention group; only 55% of seniors who were prescribed exercise but were not provided additional resources filled that particular prescription. Twenty-eight percent (10/36) participants completed the OEP three or more times per week. Fifty-three percent (19/36) completed the OEP two or more times per week. The uptake and continuation with bisphosphonates at 6-months was 56% (14/25) and that for ophthalmology referral 64% (9/14). The suggested intervention with the worst uptake was hip protectors (5%, 1/20), and this was not different between study groups (0 in the OEP group and 1 in the standard of care group). 4.3.4 Ancillary analyses I explored the estimate for the change in PPA z-score associated with Otago Exercise Program adjusted for baseline change in PPA score in participants who completed the Otago Exercise Program (10/34) at least 3 times per week (per protocol). Among compliant participants, change in PPA score was not associated with the Otago Exercise Program as measured by the t-test. Participants in the Otago Exercise Program compared with those in the standard of care group, demonstrated decreased PPA score (improvement) by 0.21 (95% CI, -0.63 to 1.1). 4.3.5 Adverse events Two participants in the Otago Exercise group reported low back pain associated with the exercises. One resumed exercising and the other discontinued the exercises. 4.4 Discussion I conducted a 6-month randomised controlled trial of a physiotherapist-initiated in-home balance and strength retraining program among 74 older persons who presented to a health care provider after a fall and who were recruited from a falls clinic. In this trial, the OEP did not improve falls risk factors significantly (PPA score, knee extension strength and sway) nor did it improve the common clinical test of gait -- the timed up and go test. However, 87 it is important to note that all of the changes in these measures were in the hypothesized direction -- toward improvement. Furthermore, evidence for the effectiveness of the intervention came in the form of a 56% reduction in falls incidence among those in the OEP group. The present study extends the findings of the only other Canadian randomized controlled trial to prevent falls [42]. In that study, Hogan and colleagues randomly allocated persons with a history of falls to a community-based consultation service to prevent falls or to usual care. Here I provide the first Canadian evidence that compared with geriatric assessment and treatment alone, geriatric assessment and treatment program combined with the Otago Exercise Program reduces seniors' rate of falls. 4.4.1 Fall incidence reduction can exceed improvement in surrogate measures of fall risk profile These results are not as incongruent as they may appear at first glance. I note that the effect size for the change in PPA z-score in the Otago Exercise group was approximately 9%, indicating decreased falls risk score. In contrast, the PPA score in the standard of care group did not change (2.0 to 2.0 over 6 months). Similarly, the effect size for the change in sway on a compliant surface with eyes open in the Otago Exercise group was approximately 17% indicating improved balance (less sway). In contrast, the sway in the standard of care group did not change. Also, there are precedents where falls incidence was reduced and surrogate measures of falls risk did not alter dramatically. Specifically with respect to the OEP, I note that the first OEP study, published in 1997, reported that the intervention was associated with a 9% improvement in balance as measured by the 4-test balance score [9]. In that study of 850 participants, this was a statistically significant improvement. The percentage improvement in this surrogate measure was of much smaller magnitude than the falls incidence rate reduction in the meta-analysis which was 35% (IRR 0.65 95% CI 0.57-0.75). Furthermore, I note that in a meta-analysis of four OEP trials a greater proportion of participants in the intervention group improved their five-time chair stand test time [10] but there was no significant improvement in knee extension strength. These important data support the finding that falls can be prevented despite modest improvements in balance and no improvement in knee extension strength. In the present study, the adjusted incidence rate ratio comparing the two study groups (0.44 (95% confidence interval 0.23 to 0.84)) is not inconsistent with that demonstrated in persons aged 80 years and older in a meta-analysis of individual level data from four New Zealand trials testing the Otago Exercise Program (0.60,95% CI 0.45-0.81) [10]. When considering that the PPA score stayed reasonably stable (within 10%) it is important to reiterate that all participants in the present study were assessed in the falls clinic prior to their enrolment in the study. I hypothesized that the falls risk profile PPA-score in the standard of care group would worsen over a 6-month period, but these scores remained unchanged. One reason this may have occurred is that clinical interventions were also suggested by the treating geriatrician at the patient's initial falls clinic visit. For example, medication rationalization, referral to ophthalmology and treatment of postural hypotension could all improve elements of the PPA score (through reaction time, contrast sensitivity, and sway, respectively). The uptake of these interventions was moderate. Also, I note that 88 half of the standard of care reported undertaking physical activity at the 6 month-follow up, When abstracting data from the clinic charts, any documentation of physical activity (including walking) in the 6-month clinic visit chart was recorded as uptake of the recommendation to seek exercise. However, the Physical Activity Scale for the Elderly questionnaire indicated that only two participants in the standard of care undertook physical activity in the form of formal balance and strength retraining. Perhaps, this increase in reported physical activity and uptake of other interventions was enough to stabilize the PPA z-score from baseline to 6 months but did not prove sufficient to decrease falls to the same extent over 12 months as the intervention group. Of course I am not in a position to address such speculation from my data. Looking at the present data alone, it would be reasonable to wonder whether the PPA instrument is a sensitive tool to detect change in fall risk profile. However, the instrument has been used in a large number or studies where it was both reliable and detected substantial changes. In women aged 75 to 85 with low bone mass, a 6-month supervised agility training or high-intensity strength training program reduced participants' PPA falls risk score by 48% and 58% respectively [43]. The participants in this study had similar mean baseline PPA z-scores to participants in the present study. Interestingly the quadriceps score component did not improve even though functional squat performance improved. To provide another example, there was significant worsening of the average PPA z-score, from 1.7 to 2.2 (23%), in a 6-month cohort study of older fallers who had presented to the emergency department [35] compared with expected age-related changes. In a recent study by Lord and colleagues, community dwelling persons aged 75 years and older were randomly allocated to an extensive individualized fall prevention program, a minimal intervention group consisting of advice or to usual care [44]. Although the PPA score was significantly decreased in the extensive intervention group compared with the usual care group, falls were not significantly reduced. Within the falls risk profile, knee extension strength and sway components remained unchanged. Adherence with the exercise component was only 23%. The significant reduction in PPA score may be due to the interventions for poor vision that were implemented in that study. Small improvements in functional measures in the elderly may nudge them above the "at-risk-threshold" for falls [45] (Prof. A. John Campbell, personal communication, March 15th, 2006). As this threshold has not been explicitly defined, it may be that a 9% improvement in falls risk score, as I found in the present study, may represent a clinically significant improvement related to falls prevention in this population. If this were the case, a sample size of 236 persons (118 per study arm) would be required to detect this difference. 89 4.4.2 Role of adherence in effective exercise interventions There are data relating exercise adherence rates and reduction of falls incidence. In five of the six OEP trials, the adherence (at least 3 times per week) ranged from 42%-63% and resulted in a significant reduction in the rate of falls [9,11,12,46]. The most recent randomized controlled trial testing the OEP, the Visually Impaired Persons (VIP) Trial, enrolled 391 visually impaired persons in a 2x2 factorial design of the OEP and occupational therapy. The adherence with the prescribed OEP (3x per week) was 18% [14]. Using an intention-to-treat analysis, falls were not significantly reduced with the OEP. However, in a per-protocol analysis, falls were significantly reduced in those who adhered with the intervention protocol. In the Vancouver falls clinic study reported here, 28% adherence with the OEP was associated with a significant 56% reduction in the rate of falls in the OEP compared with the standard of care 4.4.3 Clinical implications The relative benefits of a multifactorial intervention to reduce falls and a single intervention (such as exercise) warrant discussion given the limited health care budgets that are required to service large numbers of seniors who fall. Five multifactorial trials have been conducted among persons at high risk for future falls [29,42,47-49]. These five studies compared multifactorial intervention to usual care. The limitation of multifactorial studies is that they are essentially a "black box"- that is, it is impossible to disentangle which intervention, or combination of interventions, provided the benefit. The overall delivery of the interventions was similar across the five studies: baseline risk factors for falls were ascertained and individualized interventions strategies were recommended to the participant where indicated. The most prevalent risk factors identified were balance and strength impairments, ranging from 70-90% [29,42,47,48]. Three multifactorial studies succeeded in reducing the occurrence of falls and they provided strength and balance training [29,47,48]. Conversely, two multifactorial interventions that were not successful only recommended strength and balance retraining [42,49]. In the present study, all participants received multifactorial care and were provided with several recommendations, including one to seek physical activity that would challenge the muscle and balance systems. However, only the intervention group -- those randomized to receive the Otago Exercise Program ~ were provided with strength and balance training. In the present study, the incidence rate ratio was 0.44, and was similar to that of the multifactorial interventions where strength and balance training was delivered to the participants. Further, the rate of falls in the standard of care group was 2.8 falls per person-year, which is comparable to the rate of falls in the usual care groups across all five of the studies (ranges from 1.1 falls per person-year to 3.9 falls per person-year) [29,47,48]. These data beg the question, 'In this population, might a strength and 90 balance retraining program as a stand-alone intervention be more cost-effective than a multifactorial intervention for reducing the occurrence of falls?'. 4.4.4 Strengths, Limitations and Future Directions The strengths of this study lie in its real-world setting, the evaluation of a well-characterised exercise intervention which has previously been shown to be cost-effective in a different setting [11], and the high level of retention of participants in this age group over a one-year study. Also, the patients in this study were clearly at high risk of falls and they are described in detail because of the ancillary tests that were undertaken in the clinical setting. The study provides insight into the workings of a dedicated falls clinic and includes some novel data on the patient uptake of clinical recommendations. The over 22,000 patient days of follow-up provided the opportunity to monitor falls; we had anticipated we would be underpowered to comment on falls but nevertheless collected these data in a rigorous manner to help calculate sample size for planned future trials. All studies have limitations. The present study included fewer than 50% of patients who were seen in the falls clinic. Although the rate of recruitment was high for an exercise intervention in this population, it nevertheless must be borne in mind that we may have recruited the healthier among a frail population. I note that 38% of the persons who declined to participate declared themselves "too ill" to take part in a study. As in many studies, it would have been ideal to have a larger number of participants; nevertheless, I recruited for 18-months, assessed over 300 potential participants in a process that required a minimum of one hour for each, and completed monthly diary follow-up for a year. Because of the time constraints associated with a PhD thesis, and in consultation with my committee, I changed my initial primary outcome of falls incidence to the surrogate outcome of PPA z-score 12-months into the recruitment period. At that stage, according to pre-trial sample size calculations, I would otherwise have needed to recruit for at least another 18 months. Interestingly, the trial demonstrated a significant difference in falls incidence despite having fewer than half the participants reported in Campbell and Robertson's RCTs of the Otago Exercise Program [9,11,12]. This may be the case because sample size calculations for falls RCTs have estimated sample size based on the proportion of participants experiencing at least one fall (time to first event). However, this method ignores the potential impact of subsequent events. The potential savings in sample size if the rate of recurrence can be estimated has been discussed by Professor Cook, a noted statistician in the field of recurrent events [50]. However, if the rate of recurrence of the event has not been well documented, the sample size estimated may be incorrect. Therefore, estimating sample size based on time to first event is conservative. This illustrates the point that falls research still requires better data to improve the accuracy of sample size calculation for studies in various settings and populations, and that consultation with statisticians with expertise in the area of recurrent events would be valuable. 91 Future studies should aim to delineate the mechanism that underpins the reduction in the occurrence of falls. Candidates include the phenomenon that a small increase in risk profile might nudge participants above a 'falls threshold'. Alternatively, there may be a mechanism that is augmented by exercise and prevents falls but is not captured by the PPA or standard tests of function. Higher level brain activity such as executive function would meet those criteria. This is a fascinating area of mechanistic research that is stimulated by the finding of the present study and those other studies where surrogate measures did not explain all the variance in fall reduction. i From a practical health resource utilization perspective, given that resources are scarce, the present study begs the question of whether or not the Otago Exercise Program delivered as a stand alone intervention delivers a similar benefit in terms of falls reduction as a falls clinic that delivers standard of care including the Otago Exercise Program. I note that in New Zealand the program is designed to be coordinated from community centres without the assistance of a geriatrician in a comprehensive dedicated clinic. Such research is particularly relevant as there is a predicted shortage of not only geriatricians but also family physicians. The OEP lends itself to being provided by primary care professionals who need not be physicians. In summary, the Otago Exercise Program, initiated by experienced physiotherapists in the home environment, lowered the rate of falls in the intervention group compared with the group randomized to standard of care. The intervention did not significantly ameliorate the fall risk factor profile among community-dwelling older persons with a history of falls but there was a 9% improvement in the PPA score of the intervention group even when adherence was 28%. I conclude that the OEP is a promising intervention for seniors at high risk of falls. The present study provides local evidence for Health Authorities to adopt this intervention and extends previous Canadian data which showed that a consultation service could reduce falls. 92 Figure 4-1 CONSORT study flow diagram 308 patients assessed in falls clinic (July 7 t h 2004 - February 13th, 2006) 105 declined participation • 38 no interest • 38 too ill/caring for ill person • 21 other • 8 unable to contact 179 eligible and invited to participate 74 enrolled 74 randomized 129 ineligible 37 too healthy 46 MMSE <24 9 unable to speak English 5 falls due to syncope 3 nursing home 19 medical 10 other 36 Otago Exercise Program Lost to follow-up • 1 deceased • 1 drop-out 34 Otago Exercise Program 38 Standard of care Lost to follow-up w • 3 deceased • 3 drop-out 32 Standard of care 93 Table 4-1 Baseline demographic and clinical characteristics for the Otago Exercise Group and Standard of care Group Otago Exercise Group n=36 Standard of care Group n=38 Mean age ± SD, y 82.6 (6.1) 82.4 (6.8) Aged > 80 yrs, n (%) 25 (69) 22 (58) Female, n (%) 27 (75) 26 (68) Mean height ± SD, cm 160.0 (8.9) 162.2 (9.7) Mean weight ± SD, kg 66.5(15.2) 69.9(14.8) Living status, n (%) Alone 21 (58) 20 (53) With partner 9(25) 13(34) With Family 3(8) 4(11) Assisted living 3(8) 1(3) Referral route, n (%) Emergency department 25 (69) 27 (71) Family physician 11 (31) 11 (29) Falls clinic physician Physician A 14 (39) 16(42) Physician others 22 (61) 22 (58) Mean number falls in previous 12 month ± SD, n 1.8(1.4) 2.7 (2.7) Mean PASE score ± SD 78.4 (50) 64.2 (39) Mean GDS score ± SD 2.9 (2.4) 2.3 (2.4) Mean Barthel score ± SD 96.0 (5.2) 95.3 (6.8) Mean MMSE score ± SD 27.89(1.72) 28.03 (1.78) Mean Charlson co-morbidity score ± SD 1.5(1.5) 1.2(1.3) Mean Functional co-morbidity score ± SD 2.6(1.2) 2.6(1.7) Co-morbid conditions, n (%) Diabetes 7(19) 4(11) Thyroid condition 7(19) 7(18) COPD 5(14) 4(11) Depression 6(17) 5(13) Eye disease 17(47) 13(34) OA/RA 11 (31) 17(44) Postural hypotension 1(3) 0 Osteoporosis 16(44) 16(42) History of stroke 7(19) 8(21) Peripheral neuropathy 1(3) 9(24) Other neurological disease/condition 8(22) 4(11) Coronary artery disease 10(28) 6(16) Conqestive heart failure 3(8) 1(3) Valve disease 5(14) 3(8) Arrhythmia 10(28) 3(8T Peripheral vascular disease 2(6) 2(5) Hypertension 26 (72) 24 (63) 94 Otago Exercise Group n=36 Standard of care Group n=38 Medications Mean number of medications ± SD 5.0 (3) 5.1 (3) SSRI, n (%) 6(17) 4(11) Tricyclic, n (%) 1(3) 3(8) Other antidepressant, n (%) 1(3) 5(13) Long acting benzodiazepine, n (%) 0 1(3) Short acting benzodiazepine, n (%) 7(19) 9(24) Non-benzodiazepine hypnotic, n (%) 3(8) 2(5) Neuroleptics, n (%) 0 0 Anti-epileptic, n (%) 1(3) 3(8) Narcotic, n (%) 4(11) 6(16) Other CNS acting medication, n (%) 5(14) 5(13) Cardiovascular medication, n (%) 26 (72) 28(74) Vitamin D, n (%) 9(25) 12(32) Calcium, n (%) 9(25) 14(37) Bisphosphonates, n (%) 11 (31) 12(32) Performance Measures Timed Up and Go, sec ± SD 15.0(6.0) 20.3(14.6) Side by side stance, n (%)* 36(100) 38 (100) Semi-tandem stance, n (%)* 31 (86) 29 (76) Tandem stance, n (%)* 17(47) 15(39) Single right leg stance, n (%)* 9(25) 4(11) Single left leg stance, n (%)* 6(17) 4(11) Mean gait speed ± SD, m/sec 0.9 (0.9) 0.8(0.3) Rise from chair without hands, n (%) 30 (83) 30 (79) Mean rise from chair 5x without hands ± SD, sec ** 14.6 (5.4) 16.0 (7.7) Physiological Profile Assessment 2.2(1.3) 2.3(1.5) PPA z-Score 19.5(3.8) . 20.2 (2.6) Edge Contrast Sensitivity, dB 312.0 (73.3) 328.7 (98.8) Hand reaction time, msec 2.0(1.5) 2.1 (1.4) Proprioception, degrees 20.8 (9.2) 20.5(10.4) Knee extension strength, kg Balance parameters, mm 96.2(140.0) 138.5 (219.1) Eyes open firm surface 118.5 (61.9) 134.7 (81.6) Eyes closed firm surface 352.7 (280.3) 375.3 (342.8) Eyes open high density foam 591.1 (263.8) 537.6(161.0) Eyes closed high density foam 2.2(1.3) 2.3(1.5) Recommendations to primary care provider, n (%) Medication rationalization 13(36) 17(45) Ophthalmologist referral 9(25) 11 (29) Exercise for gait/balance/non-medication related reaction time 28 (78) 32(84) Exercise for lower limb joints 1(3) 5(13) Neurologist referral 16(44) 13(34) Cardiovascular disorder/postural hypotension/referral to 14(39) 12(32) 95 Otago Exercise Standard of care Group Group n=36 n=38 cardiologist Environmental hazard modification +/- occupational 8 (22) 10(26) therapist referral Advice re: appropriate amount of calcium 18(50) 17(45) Advice re: appropriate amount of Vitamin D 18(50) 18(47) Prescription for bisphosphonate 11 (31) 16(42) Advice re: hip protectors 13(36) 11 (29) *proportion of participants performing the test to standard (= 10 seconds), **of persons who could perform the test: n=30 OEP, n=27 standard ca 96 Table 4-2 Mean (± SD) Scores for the Physiologic Profile Assessment (PPA) and 'Timed up and Go' time at baseline and 6-months for Otago Exercise Group and Standard of care Group Otago Exercise Group Standard of care Group Baseline (n=34) 6-months (n=34) Change* Baseline (n=32) 6-months (n=32) Change* PPA z-Score 2.3(1.3) 2.1 (1.3) 0.2(1.1) 2.0(1.3) 2.0 (1.2) 0.0 (0.9) Edge Contrast Sensitivity, dB 19.4 (3.8) 19.4 (4.2) 0(1.5) 20.6(1.6) 20.3 (2.0) 0.4(1.5) Hand reaction time, msec 315.6 (72.8) 329.7(107.6) -14.1 (110.3) 317.4 (90.8) 310.6(73.4) 6.8 (58.6) Proprioception, degrees 2.0(1.5) 1.5(1.5) 0.5 (2.2) 2.1 (1.3) 1.8(1.4) 0.3 (2.2) Knee extension strength, kg 20.6 (9.2) 20.6 (9.5) 0.1 (4.3) 20.4(10.5) 20.1 (8.3) 0.3 (5.4) Balance parameters, mm Eyes open firm surface 99.3 (143.5) 81.2 (43.9) 18.1 (.121.0) 143.1 (237.6) 123.6(104.2) 19.5(218.5) Eyes closed firm surface 120.0(63.4) 111.0(38.7) 9.0 (46.4) 136.9(85.5) 158.3(104.2) -21.3(95.9) Eyes open high density foam 354.9 (285.5) 295.7(191.7) 59.2 (304.0) 318.2(253.0) 318.2(213.2) 0.1 (143.2) Eyes closed high density foam 593 (271.5) 505 (181.0) 87.2 (340.2) 532.0(175.3) 578.4(190.9) -46.4 (256.0) Mean timed up and go ± SD, sec 14.5 (4.5) 14.9 (5.6) -0.42 (3.3) 19.0(12.2) 19.8(11.4) -0.83 (6.4) *Change= (baseline value) - (6-month value) Note: PPA z-score: a positive change is associated with a decreased falls risk; Edge Contrast Sensitivity: a positive change is associated with poorer vision; hand reaction time: a positive change is associated with improved reaction time; proprioception: a positive change is associated with improved proprioception; knee extension strength: a positive change is associated with decreased strength; balance parameters: a positive change is associated with improved balance; timed up and go: a positive change is associated with a faster time C D Table 4-3 Regression table for unadjusted and adjusted values for PPA z-score, knee extension strength, sway on foam with eyes open and timed up and go (n=66). Adjusted estimates are adjusted for age, sex, referral route and falls clinic physician. Dependent Variable Independent Variable Unadjusted Estimate (SE) T Value p-value Adjusted Estimate (SE) T Value p-value PPA z-score (n=66) Group 0.13(0.23) .58 0.57 0.09 (0.22) 0.42 0.68 Baseline PPA score 0.33 (0.09) 3.77 0.0004 0.34 (0.09) 3.88 0.0003 Age, yrs -0.03 (0.018) -1.50 0.14 Sex, female 0.16(0.25) 0.66 0.51 Referral Route, ED -0.27 (0.26) -1.01 0.31 Falls Clinic Physician A 0.51 (0.23) 2.19 0.032 Knee extension strength Group 0.31 (1.1) 0.28 0.78 0.65(1.1) 0.60 0.55 Baseline KES -0.21 (0.06) -3.68 0.0005 -0.27 (0.08) -3.4 0.001 Age, yrs -0.20 (0.09) -2.3 0.03 Sex, female -1.69(1.7) -1.01 0.31 Referral Route, ED 1.5(1.3) -1.17 0.24 Falls Clinic Physician A 0.37(1.1) 0.33 0.74 Sway on foam with eyes open Group -36.6(43.1) -0.85 0.40 -31.6 (44.4) -0.71 0.48 Baseline EO sway foam -0.61 (0.08) -7.59 <0.0001 -0.61 (0.08) -7.37 <0.0001 Age, yrs 0.22 (3.6) 0.06 0.95 Sex, female -19.6(49.4) -0.40 0.69 Referral Route, ED 32.7 (52.4) 0.62 0.54 Falls Clinic Physician A -57.4 (46.4) -1.24 0.22 Timed up and go Group 1.2(1.2) 0.99 0.33 1.4(1.26) 1.13 0.26 Baseline TUG 0.18(0.07) 2.65 0.01 0.19(0.069) 2.85 0.006 Age, yrs -0.12(0.099) -1.07 0.29 Sex, female -0.94(1.35) -0.70 0.49 Referral Route, ED -0.003(1.43) 0.00 0.99 Falls Clinic Physician A 0.47(1.28) 0.37 0.72 CD OO Table 4-4 ANOVA table for unadjusted model (group and baseline score) and adjusted model (group, baseline score, age, sex, referral route, physician) for PPA z-score, knee extension strength, sway on foam with eyes open and "timed up and go" time Unadjusted model Adjusted model Dependent Variable Source DF Sum of Squares Mean Square F Value p-value DF Sum of Squares Mean Square F Value p-value PPA z-score Model 2 12.76 6.38 7.57 0.0011 6 18.88 3.15 3.96 0.0022 Error 63 53.05 0.84 59 46.93 0.80 Total 65 65.81 65 65.81 Knee extension strength Model 2 267.3 133.7 6.78 0.002 6 403.6 67.3 3.59 0.004 Error 63 1241.7 19.7 59 1105.4 18.7 Total 65 1509.0 65 1509.03 Sway on foam eyes open Model 2 1.81 x10 6 9.09 x10 5 29.78 <0.001 6 1.87x106 3.13 x 105 9.89 <0.0001 Error 63 1.92x106 3.05 x10 4 59 1.87 x10 6 3.16x10 4 Total 65 3.74x106 65 3.74x106 Timed up and go Model 2 165.4 82.7 3.59 0.03 6 209.9 35.0 1.47 0.21 Error 63 1453.11 23.1 59 1408.6 23.9 Total 65 1618.5 65 1618.5 CO C D Figure 4-2 The frequency of Physiological Profile Assessment z-score change from baseline to 6-months in the Otago Exercise Program group (group 1) and the standard of care group (group 0) Change in PPA Score histogram 1 5 j - 1 o o • - 3 -2 -1 O 2 3 1 p p a _ c h g Ml C F O NT 100 Table 4-5 Proportion (number) experiencing 0,1,2,3 and 4 or more falls during the follow-up period, incidence of fall events and follow up times in standard of care and OEP groups Falls Standard of care OEP Group n=38 n=36 0 45(17) 61 (22) 1 18(7) 25(9) 2 18(7) 3(1) 3 3(1) 6(2) 4+ 16(6) 6(2) Total number of falls observed 93 39 Total follow up time (person days) 12251 11950 Falls per person-year 277 1.19 Unadjusted Incidence rate ratio* (95% CI) 0.46 (0.2-1.1) Adjusted incidence rate ratio (95% Cl)*t 0.62 (0.3-1.4) Unadjusted incidence rate ratio*J(95% CI) 0.48 (0.2-1.0) Adjusted incidence rate ratio *ft- (95% CI) 0.44 (0.2-0.8) Compared to standard of care tadjusted for falls in the previous 12 months, sex, falls clinic physician, referral route, and age jn=71, outliers removed Table 4-6 Recommendations to primary care provider at baseline and subsequent patient uptake at 6-months of published guidelines in the Otago Exercise Group and Standard of care Group Otago Exercise Group (n=32) Standard of care Group (n=27) Intervention, n (%) Baseline 6-months Baseline 6-months Medication rationalization 11 (34) 5(45) 11 (41) 3(27)_ Ophthalmologist referral 7(22) 5(71) 7(26) 4(57) Exercise for gait/balance/non-medication related reaction time 20 (63) 17 (85) 20 (74) 11 (55) Exercise for lower limb joints 1(3) 1 (100) 4(15) 1(25) Neurologist referral 12(38) 2(17) 6(22) 0(0) Cardiovascular disorder/postural hypotension/referral to cardiologist 12 (38) 6(50) 9(33) 3(33) Environmental hazard modification +/- occupational therapist referral 5(16) 0(0) 8(30) 2(25) Advice re: appropriate amount of calcium 18 (56) 6 (33) 12(44) 5(42) Advice re: appropriate amount of Vitamin D 17(53) 7(41) 14(52) 6(43) Prescription for bisphosphonate 12(38) 9(75) 13(48) 5(39) Advice re: hip protectors 11 (34) 0(0) 9(33) 1 (11) CD Figure 4-3 Mean Cumulative Function curves and 95% confidence intervals comparing the Otago Exercise Program group (+) and the standard of care group (*) MCF estimates 103 Figure 4-4 The Mean Cumulative Function difference curve and the 95% confidence interval comparing the Otago Exercise Program group and the standard of care group MCF difference n c 2 o MCF - 1 MCF No. of Mini 1 i n N.i nl 1 Jt nt 1 N. I . i.r • In 11 ..' 36 Hu „ f 1 V l - l l t \ ? 31 Conf. Coef f . 9SX 4 ^ " 200 Tstop 104 Figure 4-5 Mean Cumulative Function curves and 95% confidence intervals comparing the Otago Exercise Program group (+) and the standard of care group (*) (n=3 outliers removed) MCF estimates iii i thou t*' put H e r s ' (h e 3) ' "  • i i n wmmm -•• " * •* *** • • •? . * * • ' 1 - - = * -7 •• jt' + + 0 100 200 300 400 Tstop grp * * * 0 +: t +• I 105 Figure 4-6 The Mean Cumulative Function difference curve and the 95% confidence interval comparing the Otago Exercise Program group and the standard of care group (n=3 outliers removed) MCF difference w i t h o u t o u t 1 Vers ( h = 3 ) 0 MCF - i n r r N o . o f U n l t s l 36 N o . o f E v e n t s 1:;: 4 S N o . o f U n i t s Z 35 No o f E v e n t s 2 ' i\ C o n f . C o n f f . asx . .:"4 . 4--.+ + + 4 . , . + +• + 200 : T s t b p ' 106 4.5 References 1. Burge, R., et al. 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ICH Expert Working Group, ICH harmonised tripartitie guideline, in Statistical Principles for Clinical Trials. 1998. 41. DeMets, D.L, Statistical issues in interpreting clinical trials. J Intern Med, 2004.255(5): p. 529-37. 42. Hogan, D, et al, A randomized controlled trail of a community-based consultation service to prevent falls. Canadian Medical Association Journal, 2001.165(5): p. 537-543. 43. Liu-Ambrose, T, et al . Resistance and agility training reduce fall risk in women aged 75 to 85 with low bone mass: a 6-month randomized, controlled trial. J Am Geriatr Soc, 2004. 52(5): p. 657-65. 44. Lord, S.R, et al . The effect of an individualized fall prevention program on fall risk and falls in older people: a randomized, controlled trial. J Am Geriatr Soc, 2005. 53(8): p. 1296-304. 45. Campbell, A .J , Preventing fractures by preventing falls in older women. Cmaj, 2002.167(9): p. 1005-6. 46. Campbell, A .J , et al . 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Stat Med, 1995.14(19): p. 2081-98. 109 5 Study 3: A systematic review of statistical methods reported in randomized controlled trials of falls prevention in older adults3 5.1 Introduction Evidence-based medicine has been promoted by the use of standards for reporting the design and methodology of randomised controlled trials (RCT). An ever-increasing number of journals are demanding that authors adhere to the Consolidated Standards for Reporting Trials (CONSORT) statement when reporting clinical trials [1]. The aim of such statements is to improve the consistency of data presentation so that readers can better assess the strengths and limitations of an RCT. To date, there are no guidelines for reporting events where the outcome can occur recurrently (e.g. falls, fractures, certain cancers and infections, chronic disease exacerbations) RCTs of falls prevention strategies commonly report the time to first event and the proportion of participants experiencing a fall. If only the time to first event is reported, as in Cox proportional hazard survival analysis, the study may conclude that the treatment is ineffective when the intervention may influence recurrence of the event (n= 2,3 and so on) (see Glynn and Buring for an example [2]). Comparing only the proportion of participants who experience a fall within a time period is analogous to a time to first event analysis. In addition, comparing proportion of participants who experience a fall discards valuable prospectively collected falls data in participants with unequal follow-up. The rate of falls is most often modelled using Poisson regression. Poisson regression assumes that events are independent, the mean and variance are equal in the population of interest and that the event rate is constant over time. These assumptions may not hold for recurrent events. When the event rates are compared using Poisson regression without accounting for the dependence of events within individuals the confidence intervals may be too narrow and the p-value too small - thus a 'truly ineffective' treatment might be reported as effective (Type I error). Several statistical models have been developed that do not require these assumptions, including negative binomial regression, the Andersen-Gill extension of the Cox model and the Wei Lin and Weissfield marginal model. Under a Poisson process, the counts of recurrent events are Poisson variants but it is often the case that they display substantial extra-Poisson variation (overdispersion)—that is, the variance is greater than the mean. Overdispersion is usually attributed to a) the dependence of events within participants or b) the dependence of events over time when previous events alter the risk of subsequent events. One approach that can be used to model the dependence within individuals is to introduce a random effect or 'frailty' variable Qifor each subject. The ai's are independent and 3 A version of this chapter has been submitted to the British Medical Journal and is currently under review. February 28 t h 2007. 110 identically distributed random variables with some distribution function G (a). Such models are referred to as random-effects, mixed-effects or frailty models. When the frailties are distributed according to a Gamma distribution the actual counts of falls then follow a negative binomial distribution. The negative binomial distribution model assumes that the event rate is constant over the intervention period. Random-effects (or frailty) models are an improvement over Poisson models-the point estimate is the same but the standard error of the estimate is increased, therefore widening the confidence intervals. However, they are not a perfect solution as these models ignore the timing of the events and cannot compensate for events clustering in the population (e.g., during an episode of acute illness such as the flu) or variations in the rate of falls over the natural course of time (e.g., seasonal variation, secular trends). For these reasons, there is utility in recurrent event analyses that consider the total number of events and their timing- including the Andersen-Gill model and the Wei, Lin and Weissfield (WLW) marginal model. The Andersen-Gill model, an extension of the Cox proportional hazards model, does not require the assumption of constant rate, or even to specify the baseline rate. The Andersen-Gill model, however, does not account for the order of the events and therefore the relationship between previous falls and subsequent falls is not dealt with explicitly. This may be crucial in falls prevention studies as a person who falls once is more likely to fall again [3]. The regression coefficient(s) (similar to the negative binomial model) estimated by the Andersen-Gill model demonstrate the treatment effect when falls (or the events of interest) within subjects are studied together without accounting explicitly for the order of events. For example, the rate estimated by the model would be the same, for example, 55% reduction be it the 1st, 2 n d, 3 r d or greater fall. The Wei, Lin and Weissfield (WLW) marginal model assumes that an individual is at risk to experience all possible events to the maximum number of events observed in the sample. For example, if the maximum number of falls observed is 10, then all participants in the WLW model are considered at risk for 10 falls even though they may not have fallen at all. The WLW model allows both the fall-specific effect of treatment to be estimated as well as the pooled effect of treatment (i.e. the average effect of the treatment over all events). The regression coefficients for the pooled and fall-specific effect of treatment can be stated as follows: The overall risk of a fall is 49% lower in the treatment group compared to the control group. The risk of a 1sl, 2"d and 3 r d fall is 49,25, and 10% lower respectively in the treatment group compared with the control group. Interestingly, the fall-specific estimates can be used to test the null hypothesis that the fall-specific regression coefficients are equal. If the null hypothesis is rejected I assume that the alternative hypothesis is true and that one or more of these coefficients are different. Estimating fall-specific coefficients may be beneficial in ascertaining the impact of the intervention of the risk for future events. Although the WLW model produces fall-specific coefficients out to the maximum number of events experienced in the sample, the interpretation of these coefficients, particularly the 3 r d, 4 t h and later events, is difficult as there may be very few participants to whom these may apply. 111 The Mean Cumulative Function (MCF) is an additional method used in recurrent event analysis which estimates the average number of events per participant over time with 95% confidence interval [4-6] and the results can be presented graphically. The MCF difference can also be calculated with its corresponding 95% confidence interval. I undertook a systematic review to assess the use of appropriate statistical methods for recurrent events used in falls prevention RCTs and to determine if the proportion of RCTs using these methods has increased from the period 1994-1999 to 2000-2006. 5.2 Methods I searched Medline for articles published between 1994 (the first successful RCT to prevent falls in community-dwelling older adults was published [7]) and November 2006 inclusive. The search query consisted of a Boolean combination of relevant text words and database subject headings describing falls prevention in community dwelling older persons (Table 3.1). The elements of the search query used to identify randomised controlled trials has been previously published [8], I included all English language articles published in peer-reviewed journals that were randomised controlled trials in community-dwelling persons aged 60 years and older that reported falls as an outcome. No assessment of quality was undertaken for each included trial. The search strategy was validated against 10 authoritative articles in the field which were identified a priori [3,7, 9-16], Included articles were also compared to references from two recent systematic reviews of falls prevention to assess sensitivity of my search strategy [17,18]. I screened the title and abstract of the selected articles for the inclusion criteria and the full articles were retrieved if relevant. These articles were assessed independently by me and a member of my committee who is a statistician. I developed a data abstraction form based on previous literature to standardize the description of methods for each study [19-21]. It included: study duration, number of drop-outs due to death, duration of follow-up time, method of falls ascertainment, graphs and statistical methods with graphical display (Table 3.2) and inferential statistics (Table 3.3) The reviewers independently read each article and completed the check-list related to statistical methods (19 items). The check-lists for both reviewers were compared for each article and discrepancies were resolved by consensus. I report the prevalence of statistical methods using recurrent events by proportion of all articles. I compared the prevalence of these methods between two publication intervals, 1994-1999 and 2000-2006 using the chi square statistic. 112 5.3 Results The flow of trials through the systematic review is displayed (Figure 5.1). Of the 84 articles included 78 (93%) were identified by the Medline search and the remaining articles were identified by the reference lists from two recent systematic reviews. The proportion of articles in the two publication intervals, 1994-1999 and 2000-2006, was 27% (23/84) and 73% (61/84) respectively. The studies included were published predominately in geriatrics and ageing journals (54%, 45/84) and general medical journals (23%, 19/84). The studies included between 18 and 5292 participants (mean 504, median 236) and reported an observation period between 5 and 260 weeks (mean 55, median 52). Nearly all studies (92%, 77/84) reported variable participant follow-up times and lost between 0 and 17% of participants due to death. The methods for ascertaining falls in the 84 studies were: monthly diary (33%, 28/84), recall at the final follow-up (33%, 28/84), weekly diary (7%, 6/84), monthly telephone call by the investigator (6%, 5/84) and weekly telephone call by the investigator (1%, 1/84). The method of ascertaining falls was not reported in 6 of the 84 studies. All 10 of the 'key' articles identified a priori by the investigators were retrieved by my search. The rate of agreement on analysis method was 91% for specified statistical methods. Discrepancies were resolved by consensus. The prevalence of the statistical methods with a graphical display by year of publication is shown in Table 5.2. The most prevalent statistical method with a graphical display was the Kaplan-Meier method (8/84) where authors estimated the cumulative probability of surviving and remaining free of a fall over the follow-up time. None of the articles included in this study used the Mean Cumulative Function to display the average number of falls per participant by a certain time. I did not observe an increase in the proportion of articles utilising graphical displays to depict recurrent events from 1994-1999 to 2000-2006. Table 5.3 details the prevalence of the inferential statistical methods by year of publication. The most prevalent inferential statistical method reported was proportion of participants having at least one fall (47/84, 56%). Fewer than one third of the articles reported at least one of the three recurrent event statistical methods (26/84). The prevalence of the negative binomial regression model, Andersen-Gill model and WLW marginal model was 25%, 7% and 4% respectively. There was no significant increase in the proportion of articles reporting negative binomial regression and marginal models. The proportion of articles reporting the Anderson-Gill model was significantly less in the period 2000-2006 compared to 1994-1999 (X2 p<0.05). 113 5.4 Discussion These findings suggest substantial under-use of three well-established statistical methods for repeated events: negative binomial regression model, Andersen-Gill model, and WLW marginal model. These methods that should underpin the analysis of recurrent events have not been used consistently; this diminishes the validity of these studies. Recurrent events are the primary outcomes in many clinical scenarios -- hospitalizations, fractures, upper respiratory tract infections, arthritis flares and asthma exacerbations. There has been considerable debate as to analysis methods for recurrent events. On the one hand, it was suggested that simply reporting the events per person-year and ignoring the dependence of multiple events within participants is seriously flawed; investigators should report only the first event, using both proportion and time to event analysis [22]. On the other hand, authors have argued for reporting the rate of recurrent events to avoid incorrect conclusions by ignoring valuable information such as when the intervention fails to impacts the first event but nevertheless influences subsequent events [2]. The mean cumulative function provides the average cumulative number of events per subject over time and the corresponding 95% confidence interval [4-6]. The MCF can be plotted and the graphs allow for an easy interpretation of the average number of events expected in one participant at a certain time. It can also illustrate (i) when interventions begin to take effect (where the curves for the intervention and control group begin to diverge), and (ii) determine on average how many events are prevented per participant by a certain time (the difference between the two curves at any given time). Finally, the mean cumulative function graph may illustrate how intervention and control groups behave over time. For example, these graphs may help to determine when an intervention is flagging (for whatever reason) and may prompt a reassessment and initiate changes to the intervention program (e.g. compliance may be a problem). To my knowledge, this is the first systematic review in falls literature to evaluate the prevalence of statistical methods. I searched Medline and used the references from two recent systematic reviews to obtain 84 articles; although I may have missed articles, it is likely that I missed both articles that did and did not utilise the three appropriate statistical methods. Although I contend that my findings have relevance to clinical conditions where outcomes occur recurrently, this study only included RCTs that reported falls. Notably, a recent systematic review of hospitalisations suggests that the appropriate statistical methods are also under-utilised [20].Therefore, I recommend that clinicians and researchers consult with statisticians with expertise in the area of recurrent event analysis to help choose an appropriate statistical model that will answer the study question. 114 Figure 5-1 Assessment of studies for includsion in RCTs of recurrent events Potentially relevant RCTs identified and abstracts screened for retrieval (n=893) RCTs retrieved for more detailed evaluation (n=113) Excluded (not RCT, age <60, not community dwelling, falls not reported) (n=780) Excluded (not RCT, age <60, not community-dwelling, falls not reported) (n=35) Included in the analysis (n=78) r Additional RCTs included from reference lists (n=6) w \ RCTs in the study group (n=84) Table 5-1 Search strategy and number of papers retained at each stage Search stage Papers retained MEDLINE search strategy: 1 clinical trial.pt. or random:.mp. or randomized controlled trial.mp. or 7313389 Randomized controlled trial.pt. 2 exp accidental falls/ 7453 3 (falls or faller$).tw. 16014 4 2 or 3 19972 5 exp aged/ 1646570 6 (older or senior$ or elderly).tw. 241395 7 5or6 1735285 8 1 and 4 and 7 1076 9 limit 8 to english language 1000 10 limit 8 to yr="1994-2006" 893 Assessment based on title and abstract 113 Assessment based on reading entire paper 78 116 Table 5-2 Statistical methods with graphical display and number of papers (prevalence) by publication year Graphical display and method used Number of papers (%) 1994-1999 n=23 2000-2006 n=61 Kaplan-Meier based approaches Time to first fall 3(13) 5(8) Mean Cumulative function based approaches 0(0) 0(0) Bar charts or pie charts Proportion of patients with stated number of falls 0(0) 4(7) Mean number of falls 0(0) 0(0) Other 0(0) 5(8) No graphical presentation of falls data 20 (87) 47(77) 117 Table 5-3 Inferential statistics and number of papers (prevalence) by publication year Inferential statistics used Number o f papers (%) 1994-1999 n=23 2000-2006 n=61 Log-rank/Proportional hazards type approaches Time to first fall 7(30) 11 (18) Proportions/Odds ratio based approaches Proportion with any falls 13(57) 34 (56) Proportion with 2 or more falls 4(17) 11 (18) Normal errors approaches (e.g. t-tests, linear regression, ANOVA) Number of falls 2(9) 15(25) Non-parametric approaches (e.g. Mann Whitney U-test) Number of falls 4(17) 7(11) Average rate of all events- relative risk based approaches 9(39) 27 (44) Negative binomial regression model 4(17) 17(28) Andersen-Gill model 4(17) 2(3)* WLW Marginal model 0(0) 3(5) Other 1(4) 3(5) No inferential statistics for falls 3(13) 1(2) Unclear what analysis has been used 2(9) 1(2) *X 2 , p<0.05 118 Table 5-4 Assumptions, strengths and limitations of three recurrent event statistical methods Method Assumption(s) Strength(s) Limitations Negative binomial regression=mixed effects Poisson Model=Random effect (frailty) model assuming a gamma distribution • Survival time is unrelated to event rate • Event rate is constant • Accommodates variable follow-up times and can adjust for other study factors • Does not consider the timing of events Andersen-Gill model • All falls (events) considered equal • Accommodates variable follow-up times and can adjust for other study factors • Can incorporate a random effect or robust standard errors • Order of events not explicitly handled Marginal model • All participants considered 'at risk' for all future events • Accommodates variable follow-up times and can adjust for other study factors • Fall-specific (event specific) and pooled treatment effects estimated • Interpretation of coefficients for later events challenging as very few participants may experience later events 119 5.5 References 1. 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Pereira, M.A, et al, A randomized walking trial in postmenopausal women: effects on physical activity and health 10 years later.[see comment] Archives of Internal Medicine, 1998.158(15): p. 1695-701. 59. Porthouse, J , et a l . Randomised controlled trial of calcium and supplementation with cholecalciferol (vitamin D3) for prevention of fractures in primary care.[see comment]. BMJ, 2005.330(7498): p. 1003. 60. Protas, E.J, et al. Gait and step training to reduce falls in Parkinson's disease. Neurorehabilitation, 2005. 20(3): p. 183-90. 61. Province, M.A, et al . The effects of exercise on falls in elderly patients. A preplanned meta-analysis of the FICSIT Trials. Frailty and Injuries: Cooperative Studies of Intervention Techniques, [see comment] JAMA, 1995. 273(17): p. 1341-7. 62. Resnick, B, Testing the effect of the WALC intervention on exercise adherence in older adults. Journal of Gerontological Nursing, 2002.28(6): p. 40-9. 63. Robertson, M.C, A.J. Campbell, and P. Herbison, Statistical analysis of efficacy in falls prevention trials. Journals of Gerontology Series A-Biological Sciences & Medical Sciences, 2005.60(4): p. 530-4. 125 64. Robertson, M.C, et al . Effectiveness and economic evaluation of a nurse delivered home exercise programme to prevent falls. 1: Randomised controlled trial.fsee comment]. BMJ, 2001.322(7288): p. 697-701. 65. Robertson, M.C, et a l . Effectiveness and economic evaluation of a nurse delivered home exercise programme to prevent falls. 2: Controlled trial in multiple centres. BMJ, 2001.322(7288): p. 701-4. 66. Robertson, M.C, et al. Preventing injuries in older people by preventing falls: a meta-analysis of individual-level data. J Am Geriatr Soc, 2002.50(5): p. 905-11. 67. Rubenstein, L Z , et al . Effects of a group exercise program on strength, mobility, and falls among fall-prone elderly men. Journals of Gerontology Series A-Biological Sciences & Medical Sciences, 2000. 55(6): p. M317-21. 68. Ryan, J.W. and A.M. Spellbring, Implementing strategies to decrease risk of falls in older women. Journal of Gerontological Nursing, 1996.22(12): p. 25-31. 69. Sattin, R.W, etal. Reduction in fear of falling through intense tai chi exercise training in older, transitionally frail adults. Journal of the American Geriatrics Society, 2005.53(7): p. 1168-78. 70. Skelton, D, et al„ Tailored group exercise (Falls Management Exercise -- FaME) reduces falls in community-dwelling older frequent fallers (an RCT). Age & Ageing, 2005. 34(6): p. 636-9. 71. Steadman, J , N. Donaldson, and L. Kalra, A randomized controlled trial of an enhanced balance training program to improve mobility and reduce falls in elderly patients. Journal of the American Geriatrics Society, 2003. 51(6): p. 847-52. 72. Steinberg, M, et al , A sustainable programme to prevent falls and near falls in community dwelling older people: results of a randomised trial. Journal of Epidemiology & Community Health, 2000.54(3): p. 227-32. 73. Stevens, M, et al. Preventing falls in older people: outcome evaluation of a randomized controlled trial. Journal of the American Geriatrics Society, 2001.49(11): p. 1448-55. 74. Suzuki, T, et al. Randomized controlled trial of exercise intervention for the prevention of falls in community-dwelling elderly Japanese women. Journal of Bone & Mineral Metabolism, 2004.22(6): p. 602-11. 75. Tinetti, M.E, et al, A multifactorial intervention to reduce the risk of falling among elderly people living in the community.[see comment] New England Journal of Medicine, 1994.331(13): p. 821-7. 76. van Haastregt, J .C, et al. Effects of a programme of multifactorial home visits on falls and mobility impairments in elderly people at risk: randomised controlled trial.jsee comment]. BMJ, 2000.321(7267): p. 994-8. 77. von Koch, L, et a l , A randomized controlled trial of rehabilitation at home after stroke in Southwest Stockholm: outcome at six months. Scandinavian Journal of Rehabilitation Medicine, 2000.32(2): p. 80-6. 78. von Koch, L, etal. Randomized controlled trial of rehabilitation at home after stroke: one-year follow-up of patient outcome, resource use and cost. Cerebrovascular Diseases, 2001.12(2): p. 131-8. 126 79. Wagner, E.H, et al . Preventing disability and falls in older adults: a population-based randomized trial. American Journal of Public Health, 1994.84(11): p. 1800-6. 80. Weerdesteyn, V , et al , A five-week exercise program can reduce falls and improve obstacle avoidance in the elderly. Gerontology, 2006. 52(3): p. 131-41. 81. Whitehead, C , et al. Evidence-based clinical practice in falls prevention: a randomised controlled trial of a falls prevention service. Australian Health Review, 2003.26(3): p. 88-97. 82. Widen Holmqvist, L, et al , A randomized controlled trial of rehabilitation at home after stroke in southwest Stockholm.[see comment]. Stroke, 1998.29(3): p. 591-7. 83. Wolf, S.L, et al. Reducing frailty and falls in older persons: an investigation of Tai Chi and computerized balance training. Atlanta FICSIT Group. Frailty and Injuries: Cooperative Studies of Intervention Techniques.[see comment] Journal of the American Geriatrics Society, 1996.44(5): p. 489-97. 84. Wolf, S.L, et al . Intense tai chi exercise training and fall occurrences in older, transitionally frail adults: a randomized, controlled trial. Journal of the American Geriatrics Society, 2003. 51 (12): p. 1693-701. 127 6 Study 4: Utility of the Mean Cumulative Function in the analysis of fall events4 6.1 Introduction As detailed in Chapter 2, falls are the most common cause of injury among elderly people. It is estimated that one in three persons over the age of 65 falls at least once each year, a proportion that increases to one in two people over the age of 80 [1, 2]. Almost half of those who fall do so recurrently [3,4]. The epidemiological literature has identified a number of risk factors for falls including age and falls in the previous year. Certain populations that seem to be particularly vulnerable to falls include residents in long-term care facilities and community dwelling persons who present to the emergency department with a fall. Although the literature suggests that falls can be prevented if intervention is directed to individuals aged 65 years and older population (e.g., persons presenting to the emergency department with a fall [5], there is also strong evidence that falls can be prevented in a population of community dwelling older persons who have been identified to be at risk for falls due to age alone [6-9]. In those aged over 80 years, there is evidence from randomized controlled trials that strength and balance retraining programs reduce seniors' risk of falls by 30% [6-9]. Interventions designed to prevent falls may also decrease the risk of subsequent fall events in an older population who have already experienced a fall [6,10]. However, it remains unclear whether such interventions prevent future falls from ever occurring or whether they delay subsequent falls, or both. Robertson and colleagues have argued, in a meta-analysis of two randomized controlled trials of the Otago balance and strength retraining program, that evaluating the efficacy of falls interventions should include analysis of all falls for each person [11] rather than simply the number of people who fall. Without these data, it is difficult to evaluate how many falls the intervention would prevent, or how long it would take for an intervention to begin to take effect. Methodologically, the possibility that an event may occur more than once in an individual over a given period of observation makes falls analysis challenging. There are several alternatives to analyzing only the first event, such as the Anderson-Gill regression model, the marginal model (Wei Lin and Weissfeld) and negative binomial regression [11,12]. However these methods do not provide an estimate of the average number of events per person within a given period of time. The Mean Cumulative Function (MCF), used for describing the average number of events occurring in one subject within a certain time, and efficient in comparing intensity of events between groups [13-15], has not previously been used to analyze multiple events in falls research. " A version of this chapter has been published. Donaldson MG, Sobolev B, Kuramoto L, Cook WL, Khan KM, Janssen PA. Utility of the Mean Cumulative Function in the analysis of fall events. J Gerontol A Biol Sci Med Sci. 2007 Apr;62(4):415-9 128 It remains unknown whether the MCF can detect differences between groups experiencing different patterns of event intensities. To learn how the MCF performs when an intervention affects the intensity of consecutive events with different patterns, I conducted simulation studies comparing MCFs among samples with different intensities of consecutive falls. We aimed to evaluate the performance of the MCF through the random simulation of multiple fall events per person. 6.2 Methods 6.2.1 Mean Cumulative Function Nelson introduced the MCF as a method to summarize the average number of events occurring in one subject within a certain time in a population exposed to censoring events such as losses to follow-up and termination of the study. It assumes that the time to events is independent from the time of censoring [15]. If a subject can only experience one event, the MCF is equivalent to the proportion of subjects ever experiencing an event. In order to define the MCF, consider n subjects who are observed over a period of time and may experience fall events at times ti, to, to.. .tN. At distinct moment tj when an event or censoring occurs, the time-dependent MCF(tj) is calculated as: MCF(tj) = • *=i  nk-\ where, is the number of events occurring at the time tk and nk.i is the number at risk just beyond time tn. The number at risk at time tn is equal to the total number initially at risk less those who were censored prior to time tn. In this setting, the risk set only decreases when a subject is removed from follow-up. 6.2.2 Simulation Studies We performed a series of Monte-Carlo simulation studies to investigate the utility of the MCF in detecting differences between four groups with different patterns of event intensity. For each group we generated a random sample of 'times of falls' (days from enrolment) among 250 subjects per group over the period of 365 days. For each subject, using an exponential distribution, we generated the number of days until the 1s l fall using the 1s t fall intensity, the number of days between the 1st and 2 n d fall using the 2 n d fall intensity, the number of days between the 2 n d and 3 r d fall using the 3 r d fall intensity and finally we generated the number of days between the 3 r d and 4 l h fall using the 4 t h fall intensity. This resulted in the distribution of subjects experiencing 0,1,2,3, or 4 falls during the period of simulation. 129 The patterns of event intensity for two groups were specified based on published data. We chose a constant average intensity of one fall per 60 and 90 days for all subsequent events in group A (control, Otago trial) and B (intervention, Otago trial) respectively [6].To our knowledge, no falls prevention studies have specifically examined the effect of the intervention on changes in the intensity of subsequent fall events. Therefore, for groups C and D we arbitrarily applied a 30% rate reduction in subsequent falls; a decrease considered clinically significant and also cost-effective [10]. The intervention groups thus were defined as follows: Groups B represents the intervention group where a long term "moderate" effect of the intervention is modeled by an average intensity of one fall per 90 days for all subsequent events [6]. Group C represents the plausible situation in an intervention, where patients comply at the outset but adhere less well with the intervention over time. To reflect this situation, the intensity of subsequent falls in Group C represents an intervention where a short term "strong" initial impact of the intervention is modeled for falls one and two, each with an average intensity of one fall per 117 days. However the effect of intervention wanes to "moderate" for falls three and four with an average intensity of one fall per 90 days. Finally, group D represents an intervention where a long term "strong" impact of the intervention is modeled by an average intensity of one fall per 117 days for all subsequent events. 6.2.3 Analysis Data were analyzed using the SAS RELIABILITY PROCEDURE (SAS Institute, Inc., Cary, North Carolina).The Mean Cumulative Function graph was generated using the MCF function in SAS. We compared groups B, C and D to group A (control) using the MCF Difference and Nelson's 95% confidence interval [14]. The MCF and the MCF difference were plotted for each comparison group. We established the approximate day when the MCF curves began to separate by determining the day at which the 95% CI of the difference no longer encompassed zero. We established the approximate day when the MCF difference curve was at its maximum. 6.3 Results The results of the simulations indicate that the MCF was able to detect differences between groups that had varying intensities of subsequent falls. During the 365 day period of simulation, the control group (group A) had a total of 937 fall events; groups B, C and D had 805,725 and 699 fall events, respectively (Table 6.2). In group A, all subjects experienced at least one fall, whereas groups B, C and D had 4,9 and 15 subjects respectively who did not experience any falls during the observation period. The proportion of subjects who had four falls declined from 84% to 40% in groups A and D respectively. 130 The MCF calculated for the control and the intervention groups showed that the average number of falls experienced by 365 days reduced from 3.75 falls per subject in group A to 2.75 falls per subject in group D. The MCF difference calculated between group A and D showed that the particular intervention attributed to group D would prevent one fall per person within 175 days on average. In addition, the MCF difference calculated between the control and the intervention groups showed that the average number of prevented falls per subject increased from group B to group D, with group D nearly achieving an additional 0.5 saved falls compared to group B. Finally, group B (moderate long-term effect) achieved its maximum benefit at day 200, whereas groups C (strong short-term effect, followed by moderate effect) and D (strong long term effect) achieved their maximum benefit 25 days earlier and with greater impact (Table 6.2). The overall pattern of the MCF difference curves, used to compare control to intervention groups, is similar. All MCF difference curves initially rise steeply to reach a peak and then gradually decline until the end of the period of observation (Figure 6.1). All groups' experience a gradual decline in the MCF difference after the maximum is achieved, however the MCF difference and the 95% confidence intervals remain above zero indicating the benefits of the intervention persist but to a lesser degree. Regardless of the intervention, after achieving their maximum MCF difference, all curves gradually declined until the end of the observation period. The MCF difference slope from time zero to time at maximum MCF difference was calculated to demonstrate the number of prevented falls per week. The number of falls prevented per week from baseline until the MCF difference reached its maximum was 0.03,0.04 and 0.05 for groups B, C and D respectively. The drop of the MCF difference from the time when the MCF difference was at a maximum to the end of the period of observation was calculated to demonstrate the number of additional falls permitted per week in each group. The drop from maximum MCF difference by 365 days was 0.013,0.01 and 0.009 additional falls per week in group B, C and D respectively. 6.4 Discussion Whether falls prevention interventions prevent falls or delay falls or both is not known. One of the challenges in assessment of fall prevention programs is that falls may occur more than once in the same subject. We have demonstrated the use of a novel instrument -- the MCF -- which allows investigators to compare the average number of falls per subject between intervention groups when the intervention reduces the intensity of subsequent falls. In this study we generated four different samples of fall times by simulating different patterns of event intensity. As expected, the most noticeable difference in the MCF was between the control group and the intervention group in which the intensity of falls decreased by 30% for falls 1 through 4 (group D).The MCF difference between the two groups showed that the particular intervention attributed to Group D would prevent on average one fall per person within 175 days. These simulation results suggest that these interventions prevented falls as several subjects in 131 groups B through D did not experience any falls during 365 days, whereas all subjects in group A experienced at least one fall. Regardless of whether the intervention was sustained across all falls (long-term effect), as in Groups B and D, or if the intervention was initially strong and then weakened over time, as in Group C, after achieving its maximum MCF difference, all curves declined gradually until the end of observation period. That is, after the maximum MCF difference was achieved, the benefit was not maintained, regardless of the simulated intervention. This information may help to guide interventions by providing information as to when exercise programs aimed at preventing falls should be re-evaluated in the study population. This concern may be addressed by adjusting the frequency, intensity, time and/or type of exercise being delivered [16]. This idea warrants further exploration and could be done by applying the MCF method to data from intervention studies. Although rarely used in health applications, the MCF has several benefits for analyzing multiple events in fall prevention literature. As the MCF is a non-parametric method it does not require assumptions about the underlying time to event distribution [15] or independence of multiple events [17]. The MCF is the average number of falls occurring in one individual over a given period; it is concerned with units (individuals) experiencing events. The Andersen-Gill, marginal Cox regression and negative binomial models, conversely, are concerned with the average rate of events over a given period. Although the MCF does not allow risk adjustment to be handled within the Reliability procedure in SAS, methods for multivariate regression analyses of the MCF are available [18]. The MCF method assumes non-informative censoring, that is individual histories of sample subjects are statistically independent of their censoring times. Although, Nelson, who described the MCF, has argued that censoring in recurrent event studies is a feature of data collection and not of the study population [15], the non-informative censoring assumption may not be applicable to falls intervention studies. It is noteworthy that moving to a long-term care facility and death are major reasons for participants withdrawing from falls studies [19]. Therefore, if continuing to live independently is a hypothetical result of balance and strength retraining, the intervention may increase the number of very frail patients who contribute data to the end of the study period. Because these patients are also more likely to have a fall, the intervention group may have more observed falls compared to the study in which losses to follow up occur independently. Therefore, informative censoring may result in an underestimation of the intervention effect. Also, several baseline factors are associated with withdrawals such as having more than one fall in the previous year, having a fall that occurred indoors (compared to falls occurring outside) and having impaired cognition [19]. These factors should be taken into consideration through appropriate randomization procedures, such as stratification. 132 This design of the simulations is a limitation of this study. I specified that the subject could experience a maximum of four falls over the simulation period. That is, if the subject experienced all four falls before the end of the simulation period (day 365), he or she would appear to be "cured" of falling, when in fact that individual should continue to have the opportunity to fall beyond day 365. I conclude that the MCF provides at least four benefits. Firstly, the MCF allows researchers to interpret how many falls an intervention would prevent, on average, in one individual over a given time period, compared to a usual care group. Secondly, the MCF naturally accommodates different follow-up times among study participants - the usual case in randomized trials. Thirdly, using the MCF can provide some evidence as to how long it takes for an intervention to begin to take effect. Finally, the MCF can be used for economic evaluation and is also applicable to costs accrued over time [15]. I recommend using the MCF to compare samples when the intensity of subsequent events varies. This method helps answer the central research question posed in falls prevention studies: Can an intervention reduce the average number of falls sustained by an individual over a period of observation and if so, by what magnitude? 133 Table 6-1 Average number of days to one fall event in groups A, 6, C and D Consecutive falls Group 1 2 3 4 Description ~A 60 60 60 60 Control [6] B 90 90 90 90 Long term moderate effect [6] C 117 117 90 90 Short term strong effect (30% decrease in intensity from moderate) followed by a moderate effect D 117 117 117 117 Long term strong effect CO -Pa. Table 6-2 Distribution of subjects by the number of falls (percent), the average number of falls per subject and the number of prevented falls by intervention group 0 falls 1 fall 2 falls 3 falls 4 falls Total falls MCF at 365 days* Prevented falls per subject! Days at max MCF differencet Max MCF differencef (MCF*) A 0 (0) 4(2) 14(6) 23 (9) 209 (84) 937 3.75 0 B 4(2) 17(7) 39(16) 50 (20) 140 (56) 805 3.25 0.50 200 0.80 (2.0) C 9(4) 38(15) 39(16) 47(19) 117(47) 725 2.90 0.85 180 1.13(1.5) D 15(6) 31 (12) 44(18) 60 (24) 100 (40) 699 2.75 1.00 175 1.15(1.5) A control B long term moderate effect C short term strong effect followed by a moderate effect D long term strong effect * average number of falls per subject f compared to Group A co cn Figure 6-1 The Mean Cumulative Function (left) and the Mean Cumulative Function difference (right). Legend: I Group A compared to Group B; II Group A compared to Group C; III Group A compared to Group D 136 6.5 References 1. Tinetti, M.E, M. Speechley, and S.F. Ginter, Risk factors for falls among elderly persons living in the community. N Engl J Med, 1988.319(26): p. 1701-7. 2. O'Loughlin, J.L, et al . Incidence of risk factors for falls and injurious falls among the community-dwelling elderly. Am J Epidemiol, 1993.137(3): p. 342-54. 3. Nevitt, M.C, et al. Risk factors for recurrent nonsyncopal falls. A prospective study. Jama, 1989.261(18): p. 2663-8. 4. Campbell, J , M. Borrie, and G. Spears, Risk factors for falls in a community-based prospective study of people 70 years and older. J Gerontol A Biol Sci Med Sci, 1989.44(4): p. M112-M117. 5. Close, J , et al. Prevention of falls in the elderly trial (PROFET): a randomized controlled trial. Lancet, 1999. 353: p. 93-97. 6. Campbell, A .J , et al . Randomized controlled trial of a general practice programme of home based exercise to prevent falls in elderly women. BMJ, 1997. 315: p. 1065-1069. 7. Campbell, A .J , et al . Psychotropic medicine withdrawl and a home-based exercise program to prevent falls: a randomized controlled trial. J Am Geriatr Soc, 1999. 47: p. 850-853. 8. Campbell, A .J , et al . Falls prevention over 2 years: a randomized controlled trial in women 80 years and older. Age Ageing, 1999.28: p. 513-518. 9. Robertson, M.C, et al . Effectiveness and economic evaluation of a nurse delivered home exercise programme to prevent falls 2: controlled trial in multiple centres. BMJ, 2001.322: p. 1-5. 10. Robertson, M, et al . Effectiveness and economic evaluation of a nurse delivered home exercise programme to prevent falls. 1: Randomised controlled trial. BMJ, 2001.322: p. 1-6. 11. Robertson, M. C , A. J. Campbell, and P. Herbison, Statistical analysis of efficacy in falls prevention trials. J Gerontol A Biol Sci Med Sci, 2005.60(4): p. 530-4. 12. Glynn, R.J. and J.E. Buring, Ways of measuring rates of recurrent events. BMJ, 1996.312(7027): p. 364-7. 13. Doganaksoy, N. and W. Nelson, A method to compare two samples of recurrence data. Lifetime Data Analysis, 1998.4(1): p. 51-63. 14. Nelson, W, Confidence limits for recurrence data: Applied to cost or number of repairs. Technometrics, 1995. 37: p. 147-157. 15. Nelson, W.B, Recurrent Events Data Analysis for Product Repairs, Disease Recurrences, and Other Applications. ASA-SIAM Series on Statistics and applied Probability, ed. R.N. Rodriguez. 2003, Philadelphia: SIAM. 151. 16. Khan, K, et al. Physical activity to prevent falls in the elderly: time to intervene in high risk groups using falls as an outcome. British Journal of Sports Medicine, 2001.35(3): p. 144-145. 17. Andersen, P.K. and R.D. Gill, Cox's regression model for counting processes: A large sample study. Ann Statistics, 1982.10: p. 1100-20. 137 18. Cook, R.J. and J.F. Lawless, Analysis of repeated events. Stat Methods Med Res, 2002.11(2): p. 141-66. 19. Close, J.C, et al. Predictors of falls in a high risk population: results from the prevention of falls in the elderly trial (PROFET). Emerg Med J, 2003.20(5): p. 421-5. 138 7 Integrated Discussion In this chapter I first provide an overview of the findings from the four studies (Chapters 3-6) that constitute my thesis. I then discuss the impact and relevance of this research for falls prevention initiatives in British Columbia. I conclude with suggestions for future research. 7.1 Overview of findings I began my thesis with a survey study to document whether or not referrals consistent with published guidelines for falls prevention were taking place after a fall-related injury. I found that the majority of women presenting to the Vancouver Hospital Emergency Department did not receive referrals recommended by current guidelines within an 18-month period after a fall-related injury. Referrals to the family physician were as low as 32%. A subsequent study by Salter and colleagues confirmed the findings from my survey study (Chapter 3); fewer than 5% of those participants reported receiving care consistent with published guidelines [1]. Particularly striking was the worsening of the average falls risk score from 1.7 to 2.2 over a 6 month observation period. However, the question remained: Why did the majority of patients not receive the standard of care (defined as care consistent with published guidelines)? One reason that may have precluded care consistent with published guidelines is that there was no single clinic to assess risk factors for falls, and to initiate clinical investigations and intervention strategies as appropriate. To address this disparity, our research group in collaboration with the Departments of Orthopaedics, Emergency Medicine, Family Practice and the Division of Geriatric Medicine, established a multidisciplinary falls clinic that would provide standardized risk factor assessment and geriatrician consultation to ensure appropriate referrals consistent with published guidelines. Patients were referred to the clinic by their family physicians; each visit took approximately 2 hours. Services to which patients were routinely referred from the falls clinic included cardiology, continence nurse, sleep clinic and ophthalmology. However, in the current medical care system in British Columbia, there is no community-based free service to deliver balance and strength retraining. Thus, to receive this from a physiotherapist a patient must pay privately. It was not known however, if the addition of balance and strength retraining to the falls clinic protocols would decrease the risk of falls. Therefore, I aimed to assess the effectiveness of the Otago Exercise Program, a balance and strength retraining program, added to the standard of care (falls clinic) compared to the standard of care alone (Chapter 4). I enrolled 74 men and women with a history of falls requiring medical attention who attended the falls clinic, with the primary aim of comparing the two study groups with respect to change in falls risk factors as assessed by the Physiological Profile Assessment z-score from baseline to 6 months. My secondary aim was to compare the occurrence of falls between the two study groups over a 12 month period. The Otago 139 Exercise Program (OEP) was associated with a 10% improvement in PPA z-score compared to the standard care group after 6 months of observation; however this difference was not statistically significant. The OEP was associated with a statistically significant 51% reduction in the rate of falls compared to the standard care alone. The magnitude of the effect in this study, for both risk factors for falls (9% improvement) and the incidence rate ratio of falls (56% reduction associated with the OEP group), are similar to the previous trials of the OEP conducted in New Zealand [2-4]. Additionally, the incidence rate ratio that I observed in my RCT is of the same magnitude as the three successful multifactorial trials of falls prevention that implemented strength and balance training as a component of their protocol [5-7]. The limitation of this study, however, is that it is only generalizable to community-dwelling persons who attend a falls clinic. It currently remains unknown if this intervention strategy would reduce the rate of falls in persons living in the institutional setting. This is the first study to examine the role of physiotherapist-initiated strength and balance retraining performed in the home environment in older people in addition to attendance at a falls clinic service that includes comprehensive geriatrician assessment. The first of these clinical studies documented the need to incorporate published guidelines in assessment and referral of older fallers who present to the emergency department with a fall. The second study provided evidence that the OEP delivered in addition to assessment and referral at a falls clinic prevented falls even though the fall risk factor profile only improved by 9%. While reviewing the falls literature, particularly the randomized controlled trials, I became interested in the statistical analysis of falls. Falls, like other health events such as colds and asthma exacerbations, are events that can occur more than once over a period of observation. I had the impression that most RCTs in the falls literature were not using methods designed to analyze recurrent events. Therefore, I conducted a systematic review of statistical methods for recurrent events in randomized controlled trials of interventions aimed to prevent falls in older adults. My systematic review indicated that fewer than one third of the studies reported using any of the three methods (negative binomial regression, Andersen-Gill extension of the Cox model and the Wei Lin and Weissfield model) developed for this purpose. This is the first systematic review of RCTs of falls prevention interventions in older adults with the specific aim of reporting the use of statistical methods for recurrent events. This study reports that the falls literature is deficient in its use of appropriate statistical methods for recurrent events and provides a summary of commonly used statistical methods for recurrent events. Although the statistical methods for recurrent events reviewed in Chapter 5 are appropriate for analyzing recurrent events, they do not provide information about the average number of falls per participant within a certain time frame. Therefore I conducted a simulation study using the Mean Cumulative Function (MCF) [8-10]. The MCF has previously been used in the reliability literature [10], but it had not previously been applied to falls—particularly in the context of comparing two simulated groups experiencing different event rates and varying times between the subsequent events. The MCF simulation study demonstrated that the MCF can detect differences among groups experiencing different rates of subsequent falls. The graphical representation of the MCF and its 95% confidence interval also demonstrates a) when an intervention begins to take effect (the point where the MCF curves for the two groups being compared diverge), b) the time when at least one fall is being prevented per person, and c) the average number of falls per person by a certain time of interest. This tool provides a useful method with graphical display to represent recurrent event comparisons. These two studies add to the falls prevention literature by underscoring the importance of utilizing relevant statistical methods to analyse recurrent events and the utility of a well developed, but underutilized method—the MCF. 7.2 Impact and relevance for falls prevention initiatives in British Columbia British Columbia's Provincial Government has identified falls prevention in older adults as an area of priority within the Ministry of Health. This Ministry has a Senior Advisor in falls prevention within the department of Prevention and Health Promotion. This position is held by Dr. Victoria Scott. Dr. Kendall (Provincial Health Officer), Dr. Peck (Deputy Provincial Health Officer) and Dr. Scott collaboratively wrote the BC government report "Prevention of falls and injuries among the elderly: A special report from the Provincial Health Officer" and this was released in January 2004 [11]. This report provided 31 recommendations for physicians, pharmacists, managers of long-term care facilities, community health worker/home care nurses and other providers of services in seniors' homes, acute care hospitals, health researchers, regional health authorities and ministries of health services and health planning. I highlight the specific recommendations for physicians and for researchers. The Provincial Health Officer's (PHO) report called upon physicians, particularly family physicians, to assume a leadership role in initiating fall prevention strategies. Specifically, the PHO report suggests that family physicians should: assess gait and balance and carry out a full assessment when necessary; engage in Continuing Medical Education about falls; encourage patients to be physically active particularly in Tai Chi and other physical activities that challenge the strength and balance systems; minimize prescription of psychotropic medications; warn patients of their high falls risk during inter-current illness; involve other physicians, such as geriatricians, as necessary; and make falls literature available to their patients in the office setting [11]. The PHO report called upon researchers to address questions regarding the type of physical activity that is most effective in preventing falls, type of physical activity that is best for seniors with chronic health conditions or disabilities, how much physical activity is enough and how to best motivate individuals to maintain health and mobility through adherence to physical activity. The report also highlighted the need for research to understand and address the barriers to physical activity in older adults. Finally, it was suggested that it was important to test the cost-effectiveness of delivering home-based exercise to older adults. Funding agencies were also encouraged to support multifactorial intervention and not to favour single intervention studies [11]. The family physician has the responsibility to initiate falls prevention; however, the standard 10-15 minute consultation allotted to each patient is not conducive to undertaking comprehensive assessment and intervention. The implementation of a falls clinic provides a clinical service that can help the family physician, or other primary care provider, to initiate this process and thus achieve the recommendation from the PHO report. The randomized controlled trial, discussed in Chapter 3, addressed the PHO recommendation for research specific to the type of physical activity that is most effective in preventing falls. The RCT did not test the effectiveness of different types of physical activity and their association with falls; rather it tested the effectiveness of a valid physical activity program delivered in the falls clinic setting. As discussed previously, the RCT undertaken in a falls clinic population demonstrated a significant decrease in the rate of falls in those who were randomized to the OEP group. 7.3 The challenge of delivering evidence-based physical activity to older adults Those who think they have not time for bodily exercise will sooner or later have to find time for illness. -Edward Stanley Lack of activity destroys the good condition of every human being, while movement and methodical physical exercise save it and preserve it. -Plato The PHO report advocates for researchers to study how much physical activity is enough and how to best motivate individuals to maintain health and mobility through adherence to physical activity. The benefits of physical activity across the lifespan are well-documented [12-14]. Regrettably, despite more than five decades of literature documenting an association between health and physical activity, data from the 1998/99 Canadian Community Health Survey reports that only 31 % of women and 41% of men in Canada over the age of 65 are moderately active (reported moderate physical activity at least 12 times per month for a minimum of 15 minutes) [15]. I would hypothesize that even fewer older Canadian are meeting the physical activity guidelines to maintain health as suggested by the US Surgeon General's Report/Center for Disease Control (30 minutes of accumulated moderate physical activity on most, preferably all, days of the week) [14]. Katzmarzyk and colleagues estimated that the cost of physical inactivity in Canada in 2001 was as high as 5.3 billion dollars [16] and that a 10% reduction in the prevalence of physical inactivity, estimated in 1991, could reduce direct health care expenditures by $150 million a year [17]. The result of a physically inactive society, Booth and colleagues argue, is an epidemic of chronic diseases [13], or, as Choi and colleagues argue, the primary cause of death in the 22nd century will be due to "diseases of comfort" [18]. 142 Physical activity interventions, like all other clinical manoeuvres, can only be effective if they are carried out with some degree of fidelity. Interventions have no opportunity to be effective if adherence is not achieved. The question remains in older adults, 'How much adherence is necessary to prevent falls?'. In my clinical trial the compliance for completing the OEP as prescribed, 3 or more times per week, was 28% and 52% of participants completed the OEP at least twice per week. The rate of adherence in my study lies between the OEP study of visually impaired persons in New Zealand that was not effective in reducing falls (compliance 3 or more times per week, 18%) and those OEP studies in New Zealand that were effective in reducing falls (compliance 3 or more times per week, 56%). In a per-protocol analysis of the study of visually impaired persons, the rate of falls was reduced amongst those who complied. This raises the following questions: How much physical activity is enough and how can adherence be enhanced? It is currently unclear how much physical activity is enough to derive benefits for falls prevention. To my knowledge, only two published exercise trials have compared varying frequencies of physical activity [19, 20], Taaffe and colleagues demonstrated that participants who engaged in high intensity resistance training once, twice or three times weekly increased in leg strength compared with participants in a control group [19], and the authors noted it was encouraging that the changes between baseline and follow-up in the three intervention groups were similar for strength outcomes. I note that this study was designed as a superiority trial and not as an equivalence trial, and the study enrolled too few participants for authors to claim equivalence. In a second study, twice weekly participation in a pre-existing community based physical activity program improved vitality (as measured by the Vitality Plus Scale) compared with a control group but once weekly participation was not significantly associated with improved measures of health [20]. Frequency of physical activity likely impacts on compliance and research into this dimension of exercise prescription - frequency - would have practical utility. Specifically, it would help researchers and clinicians better advise a largely sedentary population about physical activity. This issue is relevant to my research as I encouraged participants to undertake exercises three times weekly and to walk on other days. If comparable results can be achieved with a once-weekly program this would be popular among seniors. Also, if even better results can be obtained by increasing training frequency, would this provide even greater fall reduction? These important questions need to be addressed so that exercise prescription can be more precise. What measures can be taken to improve adherence with physical activity and in this case strength and balance retraining, recommendations? Barriers to undertaking physical activity include: increasing age, increasing disability, new health conditions, poor self-rated health and depression [21]. However, the location to undertake physical activity is may be important to facilitate adherence. In a recent study, Cyarto and colleagues found that when an identical exercise program was offered in a home-based format or a community setting, adherence was better with the home-based version [22]. Lord, Close and colleagues are studying participants' preference for home-based or group-based delivery of the Otago Exercise Program, and whether these preferences are associated with different 143 changes in falls rates and fall risk factor profile (Stephen Lord, UNSW, personal communication, January, 2007). As the OEP trials to date have only delivered the program in the home environment, it will be important to assess whether the setting for the OEP program (community vs home) affects the reduction in fall rate. Adherence to the exercise program will be a key factor to measure in falls intervention trials. Adherence may be a good marker for the acceptability of the program to a particular population. It may be necessary to expend resources to augment program adherence, by providing a van that picks individuals up three times per week to attend class at the local community center. Another example would be to fund a physiotherapist or other physical activity professional to visit the home environment three times per week on an ongoing basis to deliver the physical activity program and to continually reinforce the importance of physical activity for health. A challenge for researchers will be to measure cost-benefits of various interventions and this has been identified as a provincial research priority [11]. 7.4 Future directions There is a vast literature related to changing physician practice; it remains an area of substantial debate and the development of new approaches is ongoing [23-28] .My survey study (Chapter 3) identified that guideline care was largely absent, perhaps because there was no falls clinic to refer to. This was a catalyst for establishing a falls clinic to facilitate the delivery of care consistent with published guidelines. The RCT, conducted in participants who attended the falls clinic, adds to the literature by demonstrating that in a population of persons attending a falls clinic, the Otago Exercise Program reduced the rate of falls. However, the effect size of successful multifactorial intervention to prevent falls that delivered a physical activity component [5-7] (as opposed to merely recommending it) demonstrated effect sizes in falls reduction (approximately 30%) that were consistent with those from interventions that tested the Otago Exercise Program alone. Thus, the 'value added' of a multifactorial intervention, or a 'comprehensive geriatrician assessment' remains untested compared with provision of strength and balance training alone. Although there will be ethical and logistical challenges in undertaking such a trial, it would be interesting to see the results of a future randomized controlled trial that compared the Otago Exercise Program with the Otago Exercise Program plus falls clinic; the OEP alone may provide a similar reduction in falls and thus, prove more cost-effective. It will be important in the future to assess the role of the falls clinical service and to determine which patients are likely to benefit most. Currently, the evidence suggests that all persons with a history of falls are likely to benefit from the falls clinic [5-7]. Currently in Vancouver at a tertiary care emergency department, the only mechanism to identify patients who presented due to a fall is to manually screen the 24 hour census in the emergency department. There is no way to reliably search the electronic patient information system for fall-related presentations. Thus, case-finding is suboptimal and requires streamlining. It may be fruitful for information technologists to design data capture systems that flag these patients. However, there is the risk that there will be so many flags and mandatory codes in the system that falls may not be captured with any degree of sensitivity. It will also be important to consider automatic 144 referral to the falls clinic from the emergency department. This approach is used for referral services such as orthopaedic and vascular surgery as well as radiology. Perhaps one method to address the health needs of senior fallers is to implement dedicated preventive falls clinic services. This is now the case under the National Service Framework in the UK and within the Australian State of Western Australia. In a recent study, Christopher Beer surveyed the attitudes of family physicians to a falls clinic service in Perth, Australia. Although the family physicians were satisfied with the falls clinic service, few changed the management of their patients and many questioned whether or not the falls clinic service reduced the occurrence of falls in their patients [29]. I speculate that if family physicians were surveyed in Vancouver many would echo that sentiment. It will be important in the near future to begin to monitor fall-related injuries that occur in falls clinic patients over time after the falls clinic appointment. By doing so, falls clinics in British Columbia will then provide prospective evidence to address the concerns of health care providers regarding their effectiveness. Researchers in British Columbia are in a unique position to examine injuries requiring hospitalization because of the BC Ministry of Health Linked Health Database—all persons in the province have a unique Personal Health Number (PHN) and this number can be used to track patients' encounters with the health care system. In the last decade, British Columbia's government has increased its efforts to prevent falls and one manifestation of this was the Provincial Health Officer's report discussed above. One of the catalysts for this increasing interest was when the Ministry of Health examined hospital discharge data and recognized that the largest group of patients occupying hospital beds were older people who had sustained injurious falls. Preventive health clinics that are staffed by salaried interdisciplinary teams may provide one avenue to provide risk assessment for falls. If the protocols for this assessment are standardized, it could be performed by physiotherapists, kinesiologists, nurses, and/or occupational therapists. This model has already been adopted by the Fraser Health Authority in a novel 'mobile falls clinic' program (Fabio Feldman, personal communication, February 24, 2007). Currently in BC there are financial and access barriers that prevent older people from undertaking physical activity such as exercises that target strength and balance training. Reimbursing physiotherapist-delivered balance and strength retraining in the home-environment for older British Columbian's could provide one solution. Another solution may be to provide seniors with choices of setting (e.g., home-based or community-based) to help them obtain the recommended amount of physical activity. As well as turning the knowledge from my clinical trials into action, there are ways for the methodological studies to gain an audience. The systematic review of the statistical analyses in falls prevention RCTs illuminated a gap in use of appropriate methods. This limitation of the literature could be addressed in the future by an approach that combined education with expert review. By education, I suggest that there could be editorials and 'education' articles 145 dedicated to this point in appropriate journals. This type of article is common in the medical literature [30-36]. The level of expert statistical review in peer-reviewed journals varies; journals that employ specialist statisticians for editorial review are likely to provide more exacting review of studies with recurrent event end-points. To illustrate the point, the simulation study employing the Mean Cumulative Function [37], published in a clinical ageing journal, was reviewed by a statistician familiar with these methods. Ideally, publications in clinical journals would encourage clinician-scientists to use appropriate statistical methods. My hope is that papers including mine might make a reader aware that there is an alternate approach to recurrent event data analysis and so the individual might consult a statistician who has expertise in this area. Dedicated statistical support for clinician-scientists is essential to optimize statistical analysis in falls and other clinical sciences. At present there are no courses that include methods for analysis of recurrent events in the curriculum in the Department of Epidemiology at UBC. Given that recurrent events constitute important health outcomes (e.g., common cold, flu, asthma exacerbations, arthritis flares); such a course would be a valuable addition. In summary, I addressed two clinical questions and two methodological questions relating to falls in seniors. In each case, my research added new knowledge to the field. The finding that the OEP reduces falls in the setting of a falls clinic, the first Canadian intervention of physical activity to reduce falls in seniors, has the potential to change practice substantially. However, I have learned from both my survey and my systematic review that publications in peer-reviewed journals do not, by themselves, lead to physician behaviour change. Therefore, as I move forward through my research career, I will strive to implement knowledge exchange - turning research into action for the betterment of health. 146 7.5 References 1. Salter, A.E., et al . Community-dwelling seniors who present to the emergency department with a fall do not receive Guideline care and their fall risk profile worsens significantly: a 6-month prospective study. Osteoporos Int, 2006.17(5): p. 672-83. 2. Campbell, A .J , et al . Randomized controlled trial of a general practice programme of home based exercise to prevent falls in elderly women. BMJ, 1997.315: p. 1065-1069. 3. Robertson, M, et al . Effectiveness and economic evaluation of a nurse delivered home exercise programme to prevent falls. 1: Randomised controlled trial. BMJ, 2001. 322: p. 1-6. 4. Robertson, M.C, et al . Effectiveness and economic evaluation of a nurse delivered home exercise programme to prevent falls 2: controlled trial in multiple centres. BMJ, 2001. 322: p. 1-5. 5. Tinetti, M.E, et al , A multifactorial intervention to reduce the risk of falling among elderly people living in the community. The New England Journal of Medicine, 1994. 331(13): p. 821-827. 6. Close, J , et al. Prevention of falls in the elderly trial (PROFET): a randomized controlled trial. Lancet, 1999. 353: p. 93-97. 7. Davison, J , et a l . Patients with recurrent falls attending Accident & Emergency benefit from multifactorial intervention-a randomised controlled trial. Age Ageing, 2005. 34(2): p. 162-8. 8. Doganaksoy, N. and W. Nelson, A method to compare two samples of recurrence data. Lifetime Data Analysis, 1998. 4(1): p. 51-63. 9. Nelson, W, Confidence limits for recurrence data: Applied to cost or number of repairs. Technometrics, 1995.37: p. 147-157. 10. Nelson, W.B, Recurrent Events Data Analysis for Product Repairs, Disease Recurrences, and Other Applications. ASA-SIAM Series on Statistics and applied Probability, ed. R.N. Rodriguez. 2003, Philadelphia: SIAM. 151. 11. British Columbia Provincial Health Officer, Prevention of Falls and Inuries Among the Elderly: A Special Report from the Office of the Provincial Health Officer. 2004, British Columbia Ministry of Health: Victoria. 12. Morris, J.N, etal. Coronary heart-disease and physical activity of work. The Lancet, 1953: p. 1053-1057. 13. Booth, F, et al . Waging war on modern chronic diseases: primary prevention through exercise biology. Journal of Applied Physiology, 2000. 88: p. 774-787. 14. U.S. Department of Health and Human Services, Physical activity and health: a report of the Surgeon General. 1996, US Department of Health and Human Services, Centers for Disease Control and Prevention,National Center for Chronic Disease Prevention and Health Promotion: Atlanta, GA. 15. Statistics Canada, Census 2001, S. Canada, Editor. 2001, Government of Canada. 16. Katzmarzyk, P.T. and I. Janssen, The economic costs associated with physical inactivity and obesity in Canada: an update. Can J Appl Physiol, 2004.29(1): p. 90-115. 147 17. Katzmarzyk, P , N. Gledhill, and R. Shephard, The economic burden of physical inactivity in Canada. Canadian Medical Association Journal, 2000.163(11): p. 1435-1440. 18. Choi, B.C., et a l . Diseases of comfort: primary cause of death in the 22nd century. J Epidemiol Community Health, 2005. 59(12): p. 1030-4. 19. Taaffe, D.R, et al . Once-weekly resistance exercise improves muscle strength and neuromuscular performance in older adults. J Am Geriatr Soc, 1999.47(10): p. 1208-14. 20. Stiggelbout, M, et al. Once a week is not enough: effects of a widely implemented group based exercise programme for older adults; a randomised controlled trial. J Epidemiol Community Health, 2004.58(2): p. 83-8. 21. Burton, L.C, S. Shapiro, and P.S. German, Determinants of physical activity initiation and maintenance among community-dwelling older persons. Prev Med, 1999.29(5): p. 422-30. 22. Cyarto, E.V, W.J. Brown, and A.L. Marshall, Retention, adherence and compliance: important considerations for home- and group-based resistance training programs for older adults. J Sci Med Sport, 2006. 9(5): p. 402-12. 23. Davis, D, Continuing education, guideline implementation, and the emerging transdisciplinary field of knowledge translation. J Contin Educ Health Prof, 2006. 26(1): p. 5-12. 24. Davis, D, et al . The case for knowledge translation: shortening the journey from evidence to effect Bmj, 2003. 327(7405): p. 33-5. 25. Davis, D, et al . Impact of formal continuing medical education: do conferences, workshops, rounds, and other traditional continuing education activities change physician behavior or health care outcomes? Jama, 1999. 282(9): p. 867-74. 26. Cabana, M.D, et al . Why don't physicians follow clinical practice guidelines? A framework for improvement. Jama, 1999. 282(15): p. 1458-65. 27. Graham, I.D, et al. Lost in knowledge translation: time for a map? J Contin Educ Health Prof, 2006.26(1): p. 13-24. 28. Curry, S.J , Organizational interventions to encourage guideline implementation. Chest, 2000.118(2 Suppl): p. 40S-46S. 29. Beer, C , Attitudes of GPs to medical management in a falls clinic service. Aust Fam Physician, 2006. 35(12): p. 1008-10. 30. Altman, D. and J.M. Bland, Confidence intervals illuminate absence of evidence. Bmj, 2004. 328(7446): p. 1016-7. 31. Altman, D.G. and J.M. Bland, Absence of evidence is not evidence of absence. Bmj, 1995.311(7003): p. 485. 32. Altman, D.G. and J.M. Bland, Time to event (survival) data. Bmj, 1998. 317(7156): p. 468-9. 33. Bland, J.M. and D.G. Altman, Regression towards the mean. Bmj, 1994. 308(6942): p. 1499. 148 34. Bland, J.M. and D.G. Altman, Transformations, means, and confidence intervals. Bmj, 1996. 312(7038): p. 1079. 35. Bland, J.M. and D.G. Altman, Statistics notes. Logarithms. Bmj, 1996.312(7032): p. 700. 36. Bland, J.M. and D.G. Altman, Statistics notes. The odds ratio. Bmj, 2000. 320(7247): p. 1468. 37. Donaldson, M.G, et a l . Utility of the mean cumulative function in the analysis of fall events. J Gerontol A Biol Sci Med Sci, 2007. 62(4): p. 415-9. 149 Appendix I: Ethics Appendix II: Letter of initial contact and consent form Letter of Initial Contact Action Seniors!: A 12-month randomized controlled trial of a home based strength and balance retraining program in reducing falls Cost effectiveness analysis of a randomized controlled trial of a dedicated falls clinic intervention in elderly fallers presenting to an emergency department Date Dear Falls are one of the most common causes of injuries in older men and women. Dr. Karim Khan, a physician and researcher in the area of falls prevention, is conducting a study to improve our knowledge about the causes and treatment of falls in men and women aged 70-years or older who come to Vancouver General Hospital Emergency Department because of injuries resulting from a fall. As a result of your recent fall and medical care at Vancouver General Hospital's Emergency Department and the Falls Clinic, we would like to invite you to participate in this study. This study is investigating a program of home-delivered activity to determine whether or not it can help to prevent falls. Upon agreeing to participate in this study, you will be randomly assigned to one of two groups. Randomly assigned means that you have an equal chance of being in any group - it is like flipping a coin. If you are allocated to one group, you will receive the Otago program of stretching, strengthening and balancing activities. If allocated to the other group, you will have the opportunity to discuss factors surrounding your fall and your medical care in a Semi-structured interview. This study will involve five sessions conducted in your home by a trained instructor if you are assigned to the Otago Group or one interview conducted in your home by a trained interviewer if you are assigned to the Semi-structured Interview Group. If you are assigned to the Otago Group, the first four sessions will occur within the first two months of your involvement in the study with the fifth visit occurring at 6 months. If you are assigned to the Semi-structured interview group the interview will take place during the first month of your involvement in the study. Over the 12-month course of the study, if you are assigned to the Otago group we expect you to complete your exercise program on the schedule set by your instructor. We also require that all persons fill out and return to us a monthly fall diary. We will provide you with the monthly diary and pre-paid return envelopes. 154 Your participation in this project is entirely voluntary and will not influence your future medical care. All information will remain confidential. You will not be identifiable in any materials resulting from this study.. As Dr. Khan's research assistant, I would appreciate the opportunity to talk to you about participation in this study. I will attempt to contact you by phone on these dates and times: 1) 2) 3) If you are unavailable to speak during these times, but wish to participate, please call Meghan Donaldson at 604-875-4111 ext. 62470 and leave a message indicating a convenient time for a telephone call. Thank you in advance for your time and interest in this study. I look forward to speaking with you. Sincerely, Meghan Donaldson Research Assistant to Dr. Karim Khan and Dr. Patti Janssen University of British Columbia Phone: 604-875-4111 ext. 62470 Dr. Karim Khan Department of Family Practice University of British Columbia Phone: 604-827-4190 Dr. Patti Janssen Department of Health Care and Epidemiology University of British Columbia Phone: 604-875-2424, local 5415 155 SUBJECT INFORMATION AND CONSENT FORM Action Seniors!: A 12-month randomized controlled trial of a home based strength and balance retraining program in reducing falls Cost effectiveness analysis of a randomized controlled trial of a dedicated falls clinic intervention in elderly fallers presenting to an emergency department Principal Investigators: Dr. Karim Khan MD PhD Department of Family Practice University of British Columbia 604-827-4190 Dr. Patricia Janssen BSN PhD Department of Family Practice Department of Health Care and Epidemiology University of British Columbia 604-875-2424, local 5415 Co-investigators: Meghan Donaldson MSc. PhD Candidate Department of Health Care and Epidemiology University of British Columbia 604-875-4111, ext. 62470 Dr. Teresa Liu-Ambrose PT PhD Assistant Professor School of Rehabilitation Sciences Faculty of Medicine University of British Columbia 604-875-4111, ext 62056 Yasmin Ahamed MSc Student Department of Orthopaedics University of British Columbia 604-875-4111, ext 66314 •1. Introduction You are being invited to take part in this research study because you were seen at the Falls Clinic at BC Women's Hospital for a fall that required medical attention at Vancouver General Hospital Emergency Department. 156 Your participation in entirely voluntary, so it is up to you to decide whether or not to take part in this study. Before you decide, it is important for you to understand what the research involves. This consent form will tell you about the study, why the research is being done, what will happen to you during the study and the possible benefits, risk and discomforts. If you wish to participate, you will be asked to sign this form. If you do decide to take part in this study, you are still free to withdraw at any time and without giving any reasons for your decision. If you do not wish to participate, you do not have to provide any reasons for your decision not to participate nor will you lose the benefit of any medical care to which you are entitled or are presently receiving. Please take time to read the following information carefully and to discuss it with your family, friends, and doctor before you decide. 2. Who is conducting this study? This study is being conducted by Dr. Khan, Dr. Janssen and Ms. Donaldson of the Bone Health Research Group at the University of British Columbia. This study is partially funded by the Canadian Institutes for Health Research. There will be no involvement of any pharmaceutical company. 3. Background Falls are a common occurrence among persons over the age of 65. Approximately, 30% of people over the age of 65 will fall once during the course of a year. Falls can have serious consequences, including trauma, pain, impaired function, loss of confidence in carrying out everyday activities, loss of independence, and even death. A group of persons who may be at higher risk of falling are people who have come to an Emergency Department because of a fall. Most studies have shown that falls are reduced with physical activity programs that include strength and balance training. However, it is unknown whether persons who have had a fall that caused them to be injured can benefit from this type of physical activity. a) What is the purpose of the study? The purpose of this study is to investigate the effects of a home activity program on quality of life, muscular strength, balance and number of falls in men and women over the age of 70 years. Additionally, we hope to gather new information via interviews regarding individual's perception of their fall and the medical treatment they received for their fall. b) Who can participate in this study? You can participate in this study if you are 70 years of age and older. 157 c) Who should not participate in this study? You should not participate in this study if you have Parkinson's disease, if you currently live in an extended care facility or a nursing home or, if you are currently enrolled in a physical activity program. d) What does the study involve? This study is taking place in Vancouver, British Columbia and we plan to enroll 240 subjects for the entire study. This study will take 12 months to complete from the time you agree to participate in the study (example. If you agree to participate in June 2004, you will be enrolled until June 2005). This study may involve participating in a physical activity program that you can do in your own home. If you agree to participate, you will be randomly assigned to one of two groups: either the Otago Program or to Semi-Structured Interview. Randomly assigned means that you have an equal chance of being in any group- it is like flipping a coin. Both of these groups will be facilitated by either a trained instructor or a trained interviewer. The Otago program has been specifically designed for persons aged 60 years and older. Descriptions of both of the groups can be found below. Otago program This program will be performed three times per week in your home. Each session will take approximately 30 minutes. You will be performing a series of stretching, strengthening and balancing activities. Stretching will involve stretching all of the major muscle groups of the upper and lower body. Strengthening exercises include exercises for the upper leg, the lower leg and the hip. Balancing exercises include activities such as standing on one leg while holding on to a kitchen bench. Semi-structured Interview There will be one interview that will take approximately 45 to 90 minutes of your time, depending on the things you would like to talk about. We would like to know what you have to say about your fall and about your visit to the emergency department because of your fall. With your permission, we would like to tape record the interview so that the interviewer can concentrate on what you have to say rather than on taking notes. Everything that you tell the interviewer will be in confidence and the results of the research will be presented in general terms so that no individual person will be identified. All of the information from the conversations will be kept strictly confidential and all of the tapes from the interview will be stored in a locked filing cabinet. Only the Principal Investigators will have access to the tapes. Once the data have been analyzed, we will destroy all of the interview tapes and related information. If you agree to participate in this study, the procedures and visits you can expect will include the following: 158 e) Visits to your home For this study, we ask that you allow us to visit your home. The number of home visits that are required of you for this study depends on whether or not you are in the Otago Group or the Semi-structured Interview Group. Regardless of the group you are assigned to, everyone will receive Visit 1. Visit 1: This visit will take approximately 1.5 hours. During this visit we will ask you to answer some questions about your quality of life and, about how much physical activity you do. Together we will complete the 'Canada Safe Living Guide' to examine your home for any potential environmental hazards. Finally, we will ask you to complete a series of tasks about your reaction time, memory and attention. This visit will take approximately 1.5 hours. After you complete this visit, we will randomize (like flipping a coin) to determine which one of the two groups you will be assigned to. If you are assigned to the Otago Group: Visits 2 to 5: These visits to your home will take approximately 1 hour and will take place during your first two months in the study (e.g. a home visit every two weeks for two months). These visits are to give you proper instruction on your home program. Visit 6: This visit will take place after you have been in the study for 6 months. This visit is to ensure that you are performing the activities in your program properly. If you are assigned to the Semi-structured Interview Group: Visit 2: This visit will take approximately 45 minutes to 90 minutes of your time depending on the things you would like to talk about. During this interview we would like to ask you some questions about your fall and the treatment of your fall at the emergency department f) Visit to the Bone Health Research Lab at Vancouver Hospital At the end of the study (12 months) you will be asked to come to Vancouver Hospital for a single 3 hour appointment. During these 3 hours, you will perform all of the same tests and answer the same questionnaires as you did at the Falls Clinic at BC Women's Hospital. We will be testing your balance and your bone density. You will also answer questionnaires about your quality of life, physical activity and fear of falling. Finally, you will perform the same series of tests about memory, reaction time and attention as you did during your first home visit. g) How much of my time is required? If you agree to participate in this study you the following amount of your time is required: 1) Both groups: In-home assessment: 1.5 hours 2) Otago Group: 5 home visits by trained instructor= 5 hours Semi-structured Interview group: 1 home visit with a trained interviewed 45 to 90 minutes 159 3) Both groups: Final visit to Bone Health Laboratory at Vancouver General Hospital: 3 hours Therefore, the total amount of time required for this study over the course of 12 months, is 9.5 hours if you are assigned to the Otago group and 5.5 hours is you are assigned to the Semi-structured interview group,. If you are assigned to the Otago group, you will of course be required to complete the home activity program three times per week for 12 months, and each of these sessions takes approximately 30 minutes. h) Keeping a "Falls Calendar" We will provide you with a 12 month calendar. We will ask you to record whether or not you have had a fall as well as any visits you have had with a health care professional (e.g. family doctor, physiotherapist, emergency department doctor). If you are in the Otago group we will also ask you to record on which days you performed your home program. We will provide you with pre-addressed pre-stamped envelopes for you to send us your calendars at the end of each month. i) Your medical records If you agree to participate in this study we will ask you for permission to release your medical records from your visit at the Falls Clinic. As well, we ask that if you do have a fall during the study and you seek medical attention (e.g. a visit to your family doctor, visit to the emergency department) that we may have access to those records. We will not access your medical records for any other reason except those listed above. 4. What are the possible harms and side effects of participating? Mild physical activity is not associated with any harm to you. You may experience some muscle soreness after the first two sessions; however this should disappear after 2-3 days. 5. What are the benefits of participating in this study? No one knows whether or not you will benefit from this study. There may or may not be direct benefits to you from taking part in this study. We hope that the new knowledge we will obtain from this study can be used in the future to help prevent falls in persons over the age of 70. 6. What happens if I decide to withdraw my consent to participate? Your participation in this research is entirely voluntary. You may withdraw from this study at any time. If you decide to enter the study and to withdraw at any time in the future, there will be no penalty or loss of benefits to which you are otherwise entitled, and your future medical care will not be affected. 160 SUBJECT CONSENT TO PARTICIPATE I have read and understood the subject information and consent form. I have had sufficient time to consider the information provided and to ask for advice if necessary. I have had the opportunity to ask questions and have had satisfactory responses to my questions. I understand that all of the information collected will be kept confidential and that the result will only be used for the scientific objectives. I understand that my participation in this study is voluntary and that I am completely free to refuse to participate or to withdraw from this study at any time without changing in any way the quality of care that I receive. I understand that I am not waiving any of my legal rights as a result of signing this consent form. I understand that there is no guarantee that this study will provide any benefits to me. I have read this form and I freely consent to participate in this study. I have been told that I will receive a dated and signed copy of this form Signatures Printed name of subject Signature Date Printed name of witness Signature Date Printed name of principal investigator/ Signature Designated representative Date 162 Appendix III: Data collection forms FALL SCREEN RECORDING SHEET 1. Fall Screen Date:. 2. Fall Screen ID: 3. Falls in the past year:_ 4. Melbourne Edge Test:. 5. Proprioception 1 2 3 4 5 6. Reaction Time Trial Hand T1 T2 T3 T4 T5 1 2 3 4 5 6 7 8 9 10 Patient ID TIME TO Complete PPA 7. Quadriceps Strength Trial Strength in kg 1 2 3 8. Sway Condition AP Lateral EONF ECNF EOF ECF 9. Coordinated Stability Task 164 FALLS CLINIC Performance Measures Measure Attempted (Y/N) Time (sec) Comments Side-by-side standing Max 10 sec Semi-tandem standing Max 10 sec , Tandem standing Max 10 sec 4.0m walk (1) (2) 1x- Chair Stand 5x- Chair Stand TUG (3 m) Cane Test Scoring for the Guralnik Performance Test (Guralnik et al. NEJM1995) Standing Balance Tests: For the tests of standing balance, the subjects were asked to attempt to maintain their feet in the side-by-side, semi-tandem (heel of one foot beside the big toe of the other foot), and tandem (heel of one foot directly in front of the other foo t) positions for 10 seconds each. Score Description 0 Unable 1 Could hold a side-by-side standing position for 10 seconds but unable to hold a semi-tandem stance for 10 sec. 2 Can hold a semi-tandem position for 10 sec but unable to hold a full tandem position for more than 2 seconds 3 Can stand in the full tandem position for 3 to 9 sec. 4 Can stand in full tandem position for 10 sec. Walking: Score Description 0 Unable 1 Greater/equal to 5.7 seconds(less/equal to 0.42 m/sec) 2 4.1 - 5.6 seconds (0.44-0.60 m/sec) 3 3.2 - 4.0 seconds (0.61-0.77 m/sec) 4 Les than/equal to 3.1 seconds (greater/equal to 0.78 m/sec) Sit-to-stand: Subject is asked to fold their arms across their chest and to stand up from a sitting position once; if they can Score Description 0 Unable 1 Greater/equal to 16.7 seconds 2 13.7-16.6 seconds 3 11.2-13.6 seconds 4 Less/equal to 11.1 seconds These scores are then ADDED together to create a summary score ranging from 0 to 12. Timed Up and Go Subject is instructed to get up from a chair and walk as quickly and safely as possible, cross a line marked on the floor, turn around, walk back and sit down. The time starts as soon as the subject's back leaves the chair and the clock stops as soon as the subject's back returns to the chair. If a person uses an assistive device while walking in the community they are requested to use that device for the test. 166 ACTION SENIORS! 12 Month Falls and Medical Care Diary Thank you again for your participation in the Action Seniors! Study. Your contribution is invaluable. We ask that you keep a record of your falls and medical care throughout this study. You have been provided with 12 calendar sheets and 12 pre-paid, pre-addressed envelopes. At the end of each month we ask that you return the calendar via post. Even if you do not have any falls or medical appointments, we ask that you please return the calendar. How to fill out the calendar If you have a fall: If you have a fall please record this on the calendar with the letter 'F'. If you have a fall, please contact Meghan Donaldson as soon as possible at 604-875-4111, ext. 62470. If you receive medical care: If you receive any medical care throughout this study please mark this on your calendar as well. Medical care includes any appointment with a health professional (doctor, nurse, physiotherapist, occupational therapist) as well as seeking care at the emergency department or being hospitalised. For example, if you had a doctor's appointment for you eyes, please write "Dr. Smith, Eyes". If you have any questions at any time please feel free to call Meghan Donaldson at 604-875-4111, ext. 62470 Thank you again for your time. 167 ACTION SENIORS! 12 Month Falls, Medical Care and Otago Exercise Diary Thank you again for your participation in the Action Seniors! Study. We ask that you keep a record of your falls, medical care and Otago Exercise throughout this study. You have been provided with 12 calendar sheets and 12 pre-paid, pre-addressed envelopes. At the end of each month we ask that you return the calendar via post. Even if you do not have any falls or medical appointments, we ask that you please return the calendar. How to fill out the calendar If you have a fall: If you have a fall please record this on the calendar with the letter 'F'. Also, please contact Meghan Donaldson as soon as possible at 604-875-4111, ext. 62470. If you receive medical care: If you receive any medical care throughout this study please mark this on your calendar. Medical care includes any appointment with a health professional (doctor, nurse, physiotherapist, occupational therapist) as well as seeking care at the emergency department or being hospitalised. For example, if you had a doctor's appointment for you eyes, please write "Dr. Smith, Eyes". When you complete your Otago Exercise Program: When you complete your Otago Exercise Program, please indicate this on the calendar with the letter 'E'. If you make any changes to your exercise program (for example, omit a particular exercise), please make note of this. If you have any questions at any time please feel free to call Meghan Donaldson at 604-875-4111, ext. 62470 Thank you again for your time. 168 Charlson Comorbidity Index ID: Chart date: Assessor initials: M.E. Charlson, P. Pompei, K.L. Alex, CR . MacKenzie. A'new method of classifying prognostic comorbidity in longitudinal studies: development and validation. Journal of Chronic Diseases, vol. 40, no. 5, pp. 373-383,1987. Assigned weights for disease Condition Yes No 1 Myocardial infarct Congestive heart failure Peripheral vascular disease Cerebrovascular disease Dementia Chronic pulmonary disease Connective tissue disease Ulcer disease Mild liver disease Diabetes 2 Hemiplegia Moderate or severe renal disease Diabetes with end organ damage Any tumor Leukemia Lymphoma 3 Moderate or severe liver disease 6 Metastatic solid tumor AIDS TOTAL The total equals the score 169 The Functional Comorbidity Index ID: Chart date: Assessor initials: D i Groll, T. To, C Bombardier, J.G. Wright. The development of a comorbidity index with physical function as the outcome. Journal of clinical Epidemiology 58 (2005) 595-602. Item number Disease yes No 1 Arthritis (rheumatoid and OA) 2 Osteoporosis 3 Asthma 4 Chronic Obstructive Pulmonary Disease (COPD), acquired respiratory distress syndrome(ARDS), or emphysema 5 Angina 6 Congestive heart failure.(or heart disease) 7 Heart attack (myocardial infarct) 8 Neurological disease (such as multiple sclerosis or Parkinson's) 9 Stroke or TIA 10 Peripheral vascular disease 11 Diabetes type I and II 12 Upper gastrointestinal disease (ulcer, hernia, reflux) 13 Depression 14 Anxiety or panic disorders 15 Visual impairment (such as cataracts, glaucoma, macular degeneration) 16 Hearing impairment (very hart of hearing, even with hearing aids) 17 Degenerative disc disease (back disease, spinal stenosis or severe chronic back pain) 18 Obesity and/or body mass index > 30 (weight in kg/height in meters2) TOTAL "yes" = 1 "no" = 0 170 Post Fall Assessment FALL HISTORY Participant ID: I nterviewer: Date tall (dd/mm/yy) Date of interview (dd/mm/yy) Where were you when you fell? Classification adapted from Berg et el. (Age & Ageing 1997; 26:261) • At Home • Inside • Outside • Away from home in a familiar place • Inside • Outside • Away from home in an unfamiliar place • Inside • Outside What were you doing at the time that you fell? (check any that apply) Classification adapted from Berg et el. (Age & Ageing 1997; 26:261) • Transferring • To stand • To sit • From one seat to another • Standing • Walking • On flat surface • On an uneven surface • While holding or carrying something • While looking up or away from the ground • Stair • Climbing • Descending • Running / hurrying • On flat surface • On an uneven surface • While holding or carrying something • While looking up or away from the ground • Other (please describe): : Did you notice any symptoms before you feli? • Dizziness • Sweating • Chest discomfort • Numbness, tingling, loss of feeling • Other: • Warmth • Palpitations • Difficulty moving • New pain Did anyone witness your fall? Did you lose consciousness / black out? How much time did you spend on the ground?. Did you get up by yourself? Were you injured from your fall? Not SureY _(min) Y N Y Y (if more than one location, number the location and list the number beside the type of injury) •Soft tissue • Bruising • Laceration • Sprain / strain • Dislocation • Fracture (describe): Adapted from J Close's Fall Proforma Sheets What do you think caused your fall? Have you cut back on any of your usual activities as a result of your fall? Describe (if yes): What medical services did you seek due to your fall: Emergency Department If yes: Which ED: Were you admitted (if yes, details of services e.g. orthopaedics)?:. 422 Family Doctor Physiotherapy Additional Details of the Fall: 173 Action Seniors! Chart Review Subject ID: Chart Date: Assessor initials: I. Living status Baseline 6-months o At home o Alone o With husband/wife/partner o With family (e.g. son, daughter, niece etc.) o Assisted living o Nursing home o At home o Alone o With husband/wife/partner o With family (e.g. son, daughter, niece etc.) o Assisted living o Nursing home II. Fall history a) Date of fall (most recent or fall that flagged pt. for clinic): b) Fall within home yes/no c) Cause (check all that apply): Cause of fall Check if "yes" Slip/trip Dizzy spell LOC Palpitations Unclear d) Post fall (circle one) (Roberston MC et al. BMJ 2001): • Serious (fracture, admission to hospital with an injury or stitches) • Moderate (bruising, sprain, cut, abrasion, reduced physical function for at least 3 days, sought medical help) • No injury 174 III. Chronic Diseases at baseline (check if present) Chronic Disease Present 1. Diabetes 2. Thyroid disease 3. COPD 4. Depression 5. Eye disease 6. Arthritis (OA/RA) 7. Postural hypotension 8. Osteoporosis 9. Stroke 10. Peripheral neuropathy 11. Other neurological disease/condition 12. Coronary Artery Disease 13. Congestive Heart Failure 14. Valve disease 15. Arrhythmia 16. Peripheral vascular disease 17. Hypertension IV. Current Medication(s) (check if present) Medication Present 1. SSRI 2. Tricyclic antidepressant 3. Other antidepressants 4. Long acting benzodiazepines 5. Short acting benzodiazepines 6. Non-benzodiazepine hypnotics 7. Neuroleptics 8. Anti-epileptics 9. Narcotics 10. Other CNS acting medications 11. Cardiovascular medication 12. Vitamin D 13. Calcium 14. Bisphosphonates 15. TOTAL NUMBER of MEDS V. Risk Factors identified and suggested intervention (as per AGS/BGS/AAOS guidelines, JAGS 2001) Risk factor Risk factor present at baseline (V if present) intervention Intervention suggested at baseline (V if suggested) Intervention up-take at 6 months (V if done) Medication o Neuroleptics, benzodiazepines, and antidepressants Medication modification vision ophthalmologist Gait, balance and non-medication related reaction time Gait, balance and exercise programs Lower limb joints Gait, balance and exercise programs neurological Referral to neurologist Cardiovascular (including postural hypotension) Cardiovascular disorder treatment Postural hypotension tx. Referral to cardiologist Environmental hazards Environmental hazard modification +/-Occupational therapist referral Calcium Advice re: appropriate amount of Calcium Vitamin D Advice re: appropriate amount of Vitamin D Bisphosphonate Rx for bisphosphonate Hip protectors Advice re: hip protectors 177 Appendix IV: Questionnaires Mini Mental State Examination 1 0 What is the year? 1 0 What is the season of the year? 1 0 What is the month? 1 0 What is the date? 1 0 What is the day of the week? Can you tell me where we are, for instance: 1 0 What country are we in? 1 0 What Province is this? 1 0 What city are we in? 1 0 What is the name of this place? 1 0 What floor are we on? I am going to name three objects. After I have said them, I want you to repeat them. Remember what they are because I am going to ask you to name them again in a few minutes. 1 0 Apple 1 0 Table 1 0 Penny Now I am going to give you a word and ask you to spell it forwards and backwards. The word is WORLD. First, can you spell it forwards? Now spell it backwards please. 1 2 3 4 5 What were the three words I asked you to remember? 1 0 Apple 1 0 Table 1 0 Penny 1 1 What is this(show watch) called? 1 0 What is this (show pencil) called? 1 0 I would like you to repeat this phrase after me: "No ifs ands or buts" 1 0 I would like you to read the words on this page and then do what it says (show paper with "Close your eyes" on it). I'm going to give you a piece of paper. When I do, take the paper in your right hand, Fold it in half with both hands and drop it on the floor. 3 2 1 0 1 0 Write any complete sentence on that piece of paper for me please. 1 0 Here is a drawing. Please copy the drawing on the same paper (from Folstein, M, Folstein, SE, McHugh, PR. "mini-mental state". A practical method for grading the cognitive state of patients for the clinican. J Psychiatr Res. 1975; 12(3): 189-198) 179 CLOSE YOUR EYES 180 Please write a sentence below: Please copy the design below: Geriatric Depression Scale Shortened Version INSTRUCTIONS Undertake the test orally. Obtain a clear yes or no answer. If necessary, repeat the question. Cross off either yes or no for each question (depressive answers are bold/italicised). Count up 1 for each depressive answer. Scoring Intervals 0-4 No depression 5-10 Mild depression 11+ Severe depression 1. Are you basically satisfied with your life? Yes No 2. Have you dropped many of your activities and interests? Yes No 3. Do you feel happy most of the time? Yes No 4. Do you prefer to stay at home rather than going out and doing new things? Yes No If none of the above responses suggests depression, STOP HERE. If any of the above responses suggests depression ask questions 5-15. 5. Do you feel that life is empty? Yes No 6. Do you often get bored? Yes No 7. Are you in good spirits most of the time? Yes No 8. Are you afraid that something bad is going to happen to you? Yes No 9. Do you feel helpless? Yes No 10. Do you feel that you have more problems with memory than most? Yes No 11. Do you think it is wonderful to be alive? Yes No 12. Do you feel pretty worthless the way you are now? Yes No 13. Do you feel full of energy? Yes No 14. Do you feel that your situation is hopeless? Yes No 15. Do you think that most people are better off than you are? Yes No 182 The Barthel Index FEEDING 0 = unable 5 = needs help cutting, spreading butter, etc, or requires modified diet 10 = independent BATHING 0 = dependent 5 = independent (or in shower) GROOMING 0 = needs to help with personal care 5 = independent face/hair/teeth/shaving (implements provided) DRESSING 0 = dependent 5 = needs help but can do about half unaided 10 = independent (including buttons, zips, laces, etc.) BOWELS 0 = incontinent (or needs to be given enemas) 5 = occasional accident 10 = continent BLADDER 0 = incontinent, or catheterized and unable to manage alone 5 = occasional accident 10 = continent TOILET USE 0 = dependent 5 = needs some help, but can do something alone 10 = independent (on and off, dressing, wiping) TRANSFERS (BED TO CHAIR AND BACK) 0 = unable, no sitting balance 5 = major help (one or two people, physical), can sit 10 = minor help (verbal or physical) 15 = independent MOBILITY (ON LEVEL SURFACES) 0 = immobile or < 50 yards 5 = wheelchair independent, including corners, > 50 yards 10 = walks with help of one person (verbal or physical) > 50 yards 15 = independent (but may use any aid; for example, stick) > 50 yards STAIRS 0 = unable 5 = needs help (verbal, physical, carrying aid) 10 = independent TOTAL (0-100): 183 

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