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Markers of exacerbation severity in chronic obstructive pulmonary disease Franciosi, Luigi G; Page, Clive P; Celli, Bartolome R; Cazzola, Mario; Walker, Michael J; Danhof, Meindert; Rabe, Klaus F; Pasqua, E D O May 10, 2006

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ralssBioMed CentRespiratory ResearchOpen AcceResearchMarkers of exacerbation severity in chronic obstructive pulmonary diseaseLuigi G Franciosi*1, Clive P Page2, Bartolome R Celli3, Mario Cazzola2,4, Michael J Walker5, Meindert Danhof1, Klaus F Rabe6 and Oscar E Della Pasqua1,7Address: 1Leiden/Amsterdam Center for Drug Research, Leiden University, Leiden, The Netherlands, 2Sackler Institute of Pulmonary Pharmacology, King's College, London, UK, 3St. Elizabeth's Hospital, Tufts University, Boston, MA, USA, 4Department of Respiratory Medicine, A. Cardarelli Hospital, Naples, Italy, 5Department of Pharmacology & Therapeutics, University of British Columbia, Vancouver, Canada, 6Department of Pulmonology, Leiden University Medical Center, Leiden, The Netherlands and 7Clinical Pharmacology & Discovery Medicine, GlaxoSmithKline, Greenford, UKEmail: Luigi G Franciosi* - l.franciosi@telus.net; Clive P Page - clive.page@kcl.ac.uk; Bartolome R Celli - BCelli@copdnet.org; Mario Cazzola - mcazzola@qubisoft.it; Michael J Walker - rsdaa@interchange.ubc.ca; Meindert Danhof - m.danhof@lacdr.leidenuniv.nl; Klaus F Rabe - k.f.rabe@lumc.nl; Oscar E Della Pasqua - m.danhof@lacdr.leidenuniv.nl* Corresponding author    AbstractBackground: Patients with chronic obstructive pulmonary disease (COPD) can experience 'exacerbations' oftheir conditions. An exacerbation is an event defined in terms of subjective descriptors or symptoms, namelydyspnoea, cough and sputum that worsen sufficiently to warrant a change in medical management. There is a needfor reliable markers that reflect the pathological mechanisms that underlie exacerbation severity and that can beused as a surrogate to assess treatment effects in clinical studies. Little is known as to how existing study variablesand suggested markers change in both the stable and exacerbation phases of COPD. In an attempt to find the bestsurrogates for exacerbations, we have reviewed the literature to identify which of these markers change in aconsistent manner with the severity of the exacerbation event.Methods: We have searched standard databases between 1966 to July 2004 using major keywords and terms.Studies that provided demographics, spirometry, potential markers, and clear eligibility criteria were included inthis study. Central tendencies and dispersions for all the variables and markers reported and collected by us werefirst tabulated according to sample size and ATS/ERS 2004 Exacerbation Severity Levels I to III criteria. Due tothe possible similarity of patients in Levels II and III, the data was also redefined into categories of exacerbations,namely out-patient (Level I) and in-patient (Levels II & III combined). For both approaches, we performed a fixedeffect meta-analysis on each of the reported variables.Results: We included a total of 268 studies reported between 1979 to July 2004. These studies investigated142,407 patients with COPD. Arterial carbon dioxide tension and breathing rate were statistically differentbetween all levels of exacerbation severity and between in out- and in-patient settings. Most other measuresshowed weak relationships with either level or setting, or they had insufficient data to permit meta-analysis.Conclusion: Arterial carbon dioxide and breathing rate varied in a consistent manner with exacerbation severityPublished: 10 May 2006Respiratory Research 2006, 7:74 doi:10.1186/1465-9921-7-74Received: 05 October 2005Accepted: 10 May 2006This article is available from: http://respiratory-research.com/content/7/1/74© 2006 Franciosi et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Page 1 of 14(page number not for citation purposes)and patient setting. Many other measures showed weak correlations that should be further explored in futurelongitudinal studies or assessed using suggested mathematical modelling techniques.Respiratory Research 2006, 7:74 http://respiratory-research.com/content/7/1/74BackgroundChronic obstructive pulmonary disease (COPD) is a respi-ratory disease characterized by an airflow limitation andinflammation of the lower airways [1]. As the diseaseworsens, some patients experience 'exacerbations' of theirprincipal symptoms of dyspnoea, cough and sputum.These exacerbations frequently result in a visit to a generalpractitioner's office or to a local hospital for treatment.Exacerbations occur in COPD patients at a median ofthree times a year with half of them being unreported [2-4]. The heterogeneity of COPD exacerbations make themdifficult to define, classify and manage due to their rangeof symptoms, varied treatment requirements, seasonaloccurrence, and ambiguous aetiology [5-14].To address this problem, attempts have been made todevelop a consensus definition for COPD exacerbations[15]. Recently, the American Thoracic Society (ATS) andEuropean Respiratory Society (ERS) adopted the follow-ing definition: 'an event in the natural course of the diseasethat is characterised by a change in the patient's baseline dysp-nea, cough and sputum beyond day-to-day variability sufficientto warrant a change in management' [1].The severity of an exacerbation has been also difficult toclassify despite the various schemes that have been pro-posed to deal with this issue [4,15-17]. The ATS and ERShave also jointly suggested a classification based uponseverity and the type of medical management used, i.e.,Exacerbation Level I is home treatment, Level II is hospi-talization, and Level III is specialised care [1]. The aim ofthis scheme is to improve the existing management ofexacerbations and to serve as an aid in the assessment oftreatment efficacy.Different operational definitions for COPD exacerbationshave been proposed in the past and these have helpeddetermine their relative importance, in particular theirrelationship to COPD progression [1-17]. However, thesedefinitions have relied primarily on symptoms, and thisalong with the absence of a standard classification for thedegree of symptom severity, has delayed the developmentof new therapies for this condition. The current therapiesfor exacerbations have been evaluated based on their abil-ity to reduce symptoms, and to improve a patient's forcedexpiratory volume in one second (FEV1) since the latter isstrongly correlated with COPD mortality. However, FEV1does not discriminate well between the stable and exacer-bative states of COPD, particularly during the later stagesof this disease. Hence, the development of biologicalmarkers, or biomarkers that are more sensitive and spe-cific to the severity of COPD exacerbations would provideinvestigators with new insights and directions for furtherAt this time, only a few clinical variables or inflammatorymediators have been shown to be associated with COPDexacerbations and their related morbidity and mortality.Some of those include: age [18-20]; FEV1, forced vitalcapacity and peak expired flow [19,21,22]; body massindex [20]; albumin [20,22,23]; sodium [23]; pH [24,25];eosinophils [26-29]; interleukins 6 and 8 [29-32]; fibrin-ogen [31]; and C-reactive protein [33]. Significant clinicalevents such as the number of exacerbations per year, thenumber of hospital admissions per year, time to relapses,and days in hospital have been regarded as useful meas-ures in clinical studies designed to assess drug efficacy andcost-effectiveness as well as to standardize existing hospi-tal support programs for COPD [34-39]. However, it isnot known how these measures change with increasingseverity of COPD exacerbations.Therefore, we have surveyed the medical literature toidentify which of the commonly accepted variables andsuggested markers for COPD exacerbations changeaccording to the ATS/ERS' levels of exacerbation severity.The long-term aim of our work is to assess the sensitivityand specificity of potential markers for use in futureCOPD studies as well as to determine how such markerscan be further studied and fully integrated into the devel-opment of new drugs for COPD.MethodsSearch strategy, study selection and overall objectivesWe searched standard databases since 1966 using medicalsearch headings and related terms as obtained from majorconsensus documents related to COPD exacerbations.The major keywords were 'exacerbation', 'unstable','acute', 'bronchitis', and variants of the term 'COPD'. Thisphase of our search retrieved a total of 843 citations. Forthese citations, we read the title and abstract of each cita-tion so as to exclude citations that concerned exacerba-tions of coronary artery disease, myocardial infarction,cystic fibrosis, asthma, pulmonary emboli, and commu-nity pneumonia. Citations for case studies, letters,reviews, meta-analyses, and animal studies were alsoexcluded.After this initial screening, we identified 387 citations topapers that were of possible interest. We retrieved the orig-inal articles in electronic and hard copy forms, and thencritically read each article. As a result of this step, wearrived at a total of 268 studies in our final review andanalyses. We selected these studies based on the availabil-ity of demographics, spirometry, clear study eligibility cri-teria, and the potential markers being used to assessexacerbations.Page 2 of 14(page number not for citation purposes)research. The objectives of this literature review and data analyseswere to determine which of the baseline measures com-Respiratory Research 2006, 7:74 http://respiratory-research.com/content/7/1/74monly used in COPD exacerbation studies change withthe extent of the exacerbation and disease severity, and todetermine whether COPD exacerbations can be modelledas 'events' or 'time-to-event' in future investigations.Data abstraction methodsInitially, we considered various exacerbation definitionsand classification schemes, in particular, those suggestedby Rodriguez-Roisin [15] as well as those described byPauwels and colleagues [17]. However, we determinedthat the ATS/ERS' operational classification of exacerba-tion severity [1] was the most sensible and feasible systemfor systematically assessing the patient baseline character-istics and biomarker information from the majority ofpublished studies. We therefore used this classificationscheme and the related clinical history, physical findingsand diagnostic procedures for managing exacerbations toperform our data abstraction. From each study, weretrieved the reported demographics, spirometry, smok-ing status, clinical, cytological and biochemical variablesas well as suggested markers of the severity of the exacer-bation at baseline conditions, i.e., immediately prior to,or during the exacerbation event but before the time inwhich the intervention of interest was investigated (Table1). Whenever such variables were measured in stable con-ditions, we also abstracted this information. For eachstudy, we noted the type of definition used to define anexacerbation such as symptom- or event-based as well asthe research question asked, the experimental designused, any sponsorship, and the presence or absence ofdata from individual study patients. Data was then furtherorganized according to sample size and smoking statuswhen available. Cytological and biochemical data werealso classified according to their collection methods.These included sputum induction, bronchial biopsy,bronchoalveolar lavage (BAL), exhaled breath sampling,and blood sampling.We were also aware of the possibility that for some studygroups in severity Levels II and III (as per the ATS/ERS cri-teria) included in this review may have experienced a sim-ilar quality of care or medical management that was notreported adequately in the original publication. Inattempt to correct for this problem, we combined theexacerbation data from Levels II and III into an 'in-patient'category and then compared it to Level I that we regardedas the 'out-patient' category.Statistical methodsWe collected and calculated study means, medians, stand-ard errors, standard deviations, 95% confidence interval,and inter-quartile ranges using the statistical algorithms inMicrosoft Excel 2002. We then conducted fixed effectexacerbation level [40]. Exacerbation Severity Levels I andII, II and III, and I and III were each compared using a two-tailed Z-test. The alpha level of p < 0.05 was adjusted formultiple testing according to the Bonferroni correctionprocedure [41]. In the event that a specific exacerbationseverity level had a large number of studies in which onlymedian data were available, the data were considered tobe normally distributed and medians were treated asmeans. Since many studies did not publish data for indi-vidual patients, we were limited in addressing non-nor-mality in the data by using a log10-transformation.We again performed a fixed effect meta-analysis to obtainmean point estimates, 95% confidence intervals, and twostandard deviations for in-patient and out-patient catego-ries of each measure. We then compared each categoryusing a two-tailed Z-test and a p-value of 0.05.ResultsDescription of studies and study subjectsOur search strategy yielded 268 suitable studies that metour selection criteria. These studies were publishedbetween 1979 and July 2004 – Week 2. (The references forthese studies can be found at the LACDR Division of Phar-macology website [42]). The total number of study sub-jects included in this review was 142,407. Of this group,18% fell in Exacerbation Severity Level I, 78% in Level II,and 4% in Level III. When we re-analysed the data accord-ing to out- or in-patient settings, 18% were out-patientsand 82% in-patients.Meta-analyses of typical study demographics showed thatthere was significant overlap in 95% confidence intervalsand study data distributions for the three exacerbationseverity levels except for age where study patients in LevelII had a mean age of 64.2 years (95% confidence interval(CI): 62.9 to 65.5 years) compared to 68.0 years (95% CI:65.9 to 70.1 years) for patients in Level III (p = 0.002)(Table 2). When the demographics were re-analyzedaccording to patient settings, we determined that onlybody mass index was statistically different between theout-patient setting (mean point estimate: 26.2 kg/m2;95% CI: 23.8 to 28.7 kg/m2) and the in-patient setting(mean point estimate: 23.4 kg/m2; 95% CI: 22.5 to 24.3kg/m2) (p = 0.038) (Table 3).Relationship of different variables and biomarkers with exacerbation severity and patient settingThe spirometry measures Forced Expired Volume in 1 Sec-ond (FEV1) and Forced Vital Capacity (FVC), both in per-cent predicted, decreased from Exacerbation Levels I to II(p < 0.017) but remained unchanged from Levels II to III(Figure 1A and 1C, respectively). However, when Levels IIPage 3 of 14(page number not for citation purposes)meta-analyses to obtain mean point estimates, 95% con-fidence intervals, and two standard deviations for eachand III were combined to create an 'in-patient' categoryfor each of these variables, there was a statistically signifi-Respiratory Research 2006, 7:74 http://respiratory-research.com/content/7/1/74cant decrease for the in-patients versus the out-patients (p< 0.05) (Figure 1B and 1D, respectively). We alsoobserved the same trend for FEV1/FVC (Figure 2A and 2B).For all other spirometry measures, there were too fewstudies available in Level III for meta-analysis.different (p = 0.015) (Figure 2C). When we comparedpack years between patient settings, it was statisticallyhigher for the in-patients than the out-patients (p =0.010) (Figure 2D).In terms of the hemodynamic measures, only heart rateTable 1: Commonly Accepted Measures and Potential Markers Associated with COPD ExacerbationsDemographics Age; Gender; Height; Weight; Body Mass Index (BMI); Disease Years; Pack-Years.Spirometry/Respiratory Status Measures Forced Expired Volume in One Second – FEV1 (litres and % predicted); Forced Vital Capacity – FVC (litres and % predicted); FEV1/FVC Ratio; Breathing Rate; Oxygenation Saturation (pulse and arterial); Peak Expired Flow Rate (PEFR); Fraction of Inspired Oxygen (FiO2); Intrinsic PEEP, Arterial Oxygen Tension (PaO2); Arterial Carbon Dioxide Tension (PaCO2); PaO2/FiO2 Ratio; Sputum Production.Dyspnea Measures Baseline Dyspnea Index (BDI); Translational Dyspnea Index (TDI); Medical Research Council (MRC) Dyspnea Scale; Borg Dyspnea Score; American Thoracic Society (ATS) Dyspnea Score.Functional Challenge & Quality of Life Measures6 Minute Walking Distance (6MWD); β2-Agonist Reversibility; Adenosine Monophosphate, Methacholine or Histamine Challenge; St. George's Respiratory Questionnaire (SGRQ).Haemodynamic Measures Systolic Blood Pressure; Diastolic Blood Pressure; Arterial Blood Pressure; Heart Rate; Cardiac Output.Electrocardiogram Measures Lead II; Lead aVF; P Wave Axis-degrees.Blood Electrolyte, pH and Protein MeasuresSodium; Potassium; Chloride; Bicarbonate; Glucose; pH; Phosphate; Urea; Albumin; Haemoglobin; Creatinine.Exacerbation-Related Measures Number of Exacerbations Per Year (or in Past Year); Number of Exacerbations Per Patient-Year; Number of Exacerbations Requiring Oral Corticosteroids Per Patient-Year; Number of Exacerbation Related Infections in Past Year; Days in Hospital; Days Per Patient-Year in Hospital; Days in Intensive Care Unit; Days on Mechanical Ventilation; Number of Unscheduled or Scheduled GP Visits in Past Year; Time to First Exacerbation.Hospital-Related Measures Number of Admissions in a Year; Number of Admissions Per Patient-Year; Number of Emergency Department Visits in Past Year; Time in the Emergency Department; Number of Patients Hospitalized in Past Year; Number of Patients Readmitted in Past Year; Number of Patients Relapsed in Past Year; Ventilation Type – Non-Invasive Positive Pressure Ventilation (NIPPV), Invasive Mechanical Ventilation (IMV) or Iron Lung; Admission to ICU; Mortality in Intensive Care Unit; Mortality in Hospital; Simplified Acute Physiology II Score (SAPS II); Acute Physiology And Chronic Health Evaluation II (APACHE II); Glasgow Coma Score (GCS).Reported Comorbidities – Presence/Absence; Number & Percent of SubjectsCharlson Comorbidity Index; Cardiovascular Disease; Cor Pulmonale; Congestive Heart Failure/Insufficiency; Coronary Heart Disease; Ischaemic Heart Disease; Cardiac Arrhythmia; Hypertension; Pulmonary Oedema; Cerebrovascular Disease; Renal Disease; Liver Disease; Gastrointestinal Disease; Peripheral Vascular Disease; Endocrine Disease; Diabetes Mellitus; Cancer; Deep Vein Thrombosis; Pulmonary Emboli + Deep Vein Thrombosis; Bronchiectasis; Asthma; Depression; Emphysema; Comorbidity Present, Excluded from Study, or Not Described.Reported Causes of Exacerbations – Presence/Absence; Number & Percent of SubjectsPneumonia; Sepsis; Bronchospasm; Viral Infection; Bronchial Infection; Infection; Cardiac Insufficiency/Heart Failure; Cardiac Arrhythmia; Pulmonary Emboli; Unknown Cause.Reported Drug Information – Presence/Absence; Number & Percent of SubjectsBeta Agonists – Inhaled, Short-Acting, Long-Acting, Oral/IV Systemic; Corticosteroids – Inhaled, Oral/IV Systemic; Theophylline; Xanthines; Bronchodilators; Anticholinergics; Long-Term Oxygen Therapy (LTOT); Oxygen Supplementation; Beta-Agonist-Corticosteroid & Beta-Agonist-Anticholinergic Combinations; Antibiotics; Mucolytics; Expectorants; Antitussives; Diuretics; Oral Anticoagulants; Patient Compliance.Bacterial Information – Number of Patients/Number of IsolatesS. pneumoniae; H. influenzae; M. catarrhalis; P. aeruginosa; B. catarrhalis; H. parainfluenza; S. aureus; C. pneumoniae; E. coli; OTHER: K. pneumoniae, Enterobacteriaceae, Pseudomonas Species, Alpha-Haemolytic Streptococci, Acinetobacter, M. pneumoniae, Legionella Species.Viral Information – Number of Patients/Number of IsolatesInfluenza Virus A & B; Parainfluenza V1, V2 & V3; Adenovirus; Respiratory Syncytial Virus (RSV); Picornavirus; Rhinovirus; Coronavirus.Cytological Measures – Local (Sputum, Bronchoalveolar Lavage (BAL), Biopsy); Systemic (Plasma or Serum)Neutrophils; Macrophages; Eosinophils; Lymphocytes (White Blood Cells).Biochemical Measures – Local (Exhaled, Sputum, BAL, Biopsy); Systemic (Plasma or Serum)Leukotriene B4 (LTB4); 8-Isoprostane (8IPT); Elastase; Myeloperoxidase (MPO); Secretory Leukoprotease Inhibitor (SLPI); Endothelin-1 (ET-1); Interleukin-8 (IL8); Interleukin-6 (IL6); Interleukin-10 (IL10); Nitric Oxide; Tumour Necrosis Factor (TNFα); C-Reactive Protein (CRP); Fibrinogen.Many study variables were measured at or around the time of the exacerbation. If these variables were measured in the stable condition of these COPD patients, i.e., measurements were taken weeks or months prior to the exacerbation, then these were also obtained.Page 4 of 14(page number not for citation purposes)We found for smoking that pack years increased with exac-erbation severity, but only Levels I and II were statisticallyshowed a statistically significant difference being higherin Level II than Level I (p = 0.014) with no differenceRespiratory Research 2006, 7:74 http://respiratory-research.com/content/7/1/74between Levels II and III (Figure 3A). Heart rates were alsohigher for in-patients than out-patients (p = 0.011) (Fig-ure 3B).The clinical measures of dyspnoea, i.e., the breathing rate(Figure 3C) and Borg dyspnoea score, tended to increasefrom Levels I to II and then decrease from Levels II to III.However, only breathing rate demonstrated clear statisti-cal differences between the three levels (p < 0.017). OnlyLevels II and III of the Borg Dyspnoea Score were statisti-cally different (p < 0.001); a statistical comparison ofthese levels with Level I was not possible due to lack ofdata. When patient settings were compared, only breath-ing rate showed a clear statistical difference being statisti-cally lower for in-patients than out-patients (p = 0.003)(Figure 3D).Exacerbation Levels II and III were statistically differentbicarbonate increased. However, there was insufficientLevel I data for each variable to allow for statistical com-parisons with the other Levels. There was also insufficientdata available to compare out-patients with in-patients.In terms of blood gas measures studied, only arterial car-bon dioxide tension (PaCO2) showed a statistically signif-icant increase with increasing exacerbation severity (p <0.017) (Figure 4A) as well as out- versus in-patients (p <0.05) (Figure 4B). In the case of oxygen saturation, it grad-ually decreased with increasing exacerbation severity withstatistically significant differences between Levels I and II(p < 0.001) as well as Levels I and III (p = 0.011) (Figure4C). It also decreased going from an out-patient to an in-patient setting (P < 0.001) (Figure 4D).The six minute walking distance challenge test seemed toshow a decreasing trend with increasing exacerbationTable 2: Typical Subject Demographics According to ATS/ERS 2004 Exacerbation Severity LevelVariable/Exacerbation Severity Level†Total Studies* Total Subjects# Point Estimate (95% CI)Study Data Distributions (± 2SD)Significance Test‡Z Test P ValueAge (years) 182 27,930 LevelsLevel I 71 16,917 66.0 (64.6 – 67.4) 51.2 – 80.8 I vs. II 0.067 (NS)Level II 70 7,300 64.2 (62.9 – 65.5) 52.1 – 76.3 II vs. III 0.002Level III 43 3,713 68.0 (65.9 – 70.1) 53.0 – 83.0 I vs. III 0.12 (NS)Height (cm) 27 3,154 LevelsLevel I 14 2,581 169.7 (166.4 – 173.0) 155.1 – 184.3 I vs. II 0.25 (NS)Level II 9 247 167.1 (164.0 – 170.2) 157.5 – 176.6 II vs. III 0.54 (NS)Level III 4 326 169.1 (163.4 – 174.7) 157.3 – 180.9 I vs. III 0.85 (NS)Weight (kg) 37 4,168 LevelsLevel I 15 3,176 72.8 (67.5 – 78.1) 46.9 – 98.7 I vs. II 0.36 (NS)Level II 12 290 69.3 (63.8 – 74.7) 49.4 – 89.1 II vs. III 0.26 (NS)Level III 10 702 63.6 (55.3 – 71.9) 35.5 – 91.7 I vs. III 0.067 (NS)Body-Mass Index (kg/m2) 29 4,250 LevelsLevel I 6 2,273 26.2 (23.8 – 28.7) 18.5 – 34.0 I vs. II 0.037 (NS)Level II 19 1,729 23.4 (22.4 – 24.4) 19.5 – 27.3 II vs. III 0.84 (NS)Level III 7 248 23.6 (21.2 – 26.0) 17.1 – 30.1 I vs. III 0.14 (NS)Disease Years 21 8,606 LevelsLevel I 15 8,354 10.9 (7.8 – 14.1) 0 – 26.4 I vs. II 0.65 (NS)Level II 5 228 12.9 (5.0 – 20.8) 0 – 30.2 II vs. III 0.67 (NS)Level III 2 24 16.2 (3.9 – 28.4) 0 – 33.5 I vs. III 0.42 (NS)Symbols and Abbreviations: *Bold numbers indicate total studies (without duplicates) for the specific variable of interest; # Bold numbers indicate total subjects for all COPD exacerbation severity levels with respect to the specific variable of interest; † Exacerbation severity levels are based on the following ATS/ERS 2004 operational classification scheme: Level I – treated at home; Level II – requires hospitalisation ; and Level III – leads to respiratory failure; ‡ Exacerbation Levels II and III were each compared to Level I using a two-tailed Z-test in which the alpha level was adjusted according to the Bonferroni Correction procedure to account for multiple testing; and NS = Non-significant difference.Page 5 of 14(page number not for citation purposes)with respect to pH (p = 0.003) and bicarbonate (p =0.002) in that pH decreased from Level II to III whereasseverity but such changes did not reach statistical signifi-cance. This was also the case when the out- and in-patientsRespiratory Research 2006, 7:74 http://respiratory-research.com/content/7/1/74were compared. Many other variables related to spirome-try, respiratory status, exacerbation and hospital event cat-egories also did not change significantly withexacerbation severity or out- and in-patients (See addi-tional file 1). There was not enough data in the bacteriol-ogy and virology categories to permit any meta-analyses.Of the 268 studies sampled, only half contained dataabout the biochemical variables.DiscussionWe conducted this review of the COPD exacerbation liter-ature to determine which commonly-accepted baselinevariables and suggested markers changed in a consistentmanner with the severity of COPD exacerbations. As ourindex of COPD severity, we used the recently publishedATS/ERS operational classification of exacerbation sever-ity for medical management. This is because most of thepublished literature rarely provides sufficient details tocharacterise the severity of a patient's exacerbation. Inaddition, we also analyzed the same data according toout- and in-patient settings so as to account for possibleoverlaps in medical management between Levels II and IIIbut were not reported in the original publication.The long-term aim of our work is to improve the qualityand applicability of exacerbation management throughthe identification of sensitive and specific markers thatcan be used for the assessment of treatment effects. Thisreview identified a few potential markers of exacerbationseverity.When we assessed the spirometry measures FEV1 and FVCin % predicted, as well as FEV1/FVC, we observed statisti-cally significant differences with exacerbation severity,and between out- and in-patients (Figures 1A–D and 2A–B). One draw-back was the paucity of such information inLevel III studies. This confirms the clinical situation thatas exacerbations worsen and more specialised care isrequired, spirometry measurements are less likely underbaseline conditions or during an exacerbation [14]. Thus,such data is rare in many published studies.The number of smoking-related pack years increased withexacerbation severity and showed a clear differencebetween out- and in-patient settings (Figures 2C and 2D),a finding that is consistent with the idea that the more aCOPD patient smokes, and for longer, the higher the like-Table 3: Typical Subject Demographics According to Out-Patient and In-patient SettingsVariable/Patient Setting Type†Total Studies* Total Subjects# Point Estimate (95% CI)Study Data Distributions (± 2SD)Significance Test‡Z Value P ValueAge (years) 182 27,930 0.78 0.44 (NS)Out-patient 71 16,917 66.0 (64.6 – 67.4) 51.2 – 80.8In-patient 112 11,013 65.3 (64.2 – 66.4) 52.3 – 78.3Height (cm) 27 3,154 1.00 0.32 (NS)Out-patient 14 2,581 169.7 (166.4 – 173.0) 155.1 – 184.3In-patient 13 573 167.5 (164.8 – 170.2) 157.5 – 177.6Weight (kg) 37 4,168 1.48 0.14 (NS)Out-patient 15 3,176 72.8 (67.5 – 78.1) 46.9 – 98.7In-patient 22 992 67.5 (62.9 – 72.1) 45.1 – 89.9Body-Mass Index (kg/m2)29 4,250 2.08 0.038Out-patient 6 2,273 26.2 (23.8 – 28.7) 18.5 – 34.0In-patient 24 1,977 23.4 (22.5 – 24.3) 19.1 – 27.7Disease Years 21 8,606 0.78 0.44 (NS)Out-patient 15 8,354 10.9 (7.8 – 14.1) 0 – 26.4In-patient 6 252 13.9 (7.1 – 20.7) 0 – 31.7Symbols and Abbreviations: *Bold numbers indicate total studies (without duplicates) for the specific variable of interest; # Bold numbers indicate total subjects for out-patient and in-patient categories with respect to the specific variable of interest; † Out-patient category represents ATS/ERS 2004 Exacerbation Severity Level I (treated at home) and the in-patient category Levels II (requires hospitalisation) and III (leads to respiratory failure) combined; ‡ Outpatient and in-patient categories were compared using a two-tailed Z-test; and NS = Non-significant difference.Page 6 of 14(page number not for citation purposes)lihood that COPD exacerbations will be more severe.According to the mean point estimates obtained in thisRespiratory Research 2006, 7:74 http://respiratory-research.com/content/7/1/74Page 7 of 14(page number not for citation purposes)Fixed Effect Meta-Analysis Results of Selected Spirometry Variablesigure 1Fixed Effect Meta-Analysis Results of Selected Spirometry Variables. Graphs displayed are: A) FEV1 % Predicted (COPD Exacerbation Severity Levels I to III); B) FEV1 % Predicted (Out- versus In-patient Setting); C) FVC % Predicted (Levels I to III); and D) FVC % Predicted (Out- versus In-patient Setting). For each spirometry variable, the point estimates (point), 95% confidence intervals (box), and two standard deviations (bars) are presented for Levels I to III and out- & in-patient settings. 'N' signifies the total studies and 'n' is the total subjects. P < 0.017 is indicated for statistical comparisons of Level I versus II (*), II versus III (†), and I versus III (#) as well as P < 0.05 for comparison of out- versus in-patient setting (*).10 20 30 40 50 60 70 80 90 100 Level I(N=23;n=1181) Level II(N=28;n=1728) Level III(N=5;n=446)FEV1 (% Predicted)*#A10 20 30 40 50 60 70 80 90 100 Out-patient(N=23;n=1181) In-patient(N=33;n=2174)FEV1 (% Predicted)*B20 30 40 50 60 70 80 90 Level I(N=8;n=402) Level II(N=7;n=176) Level III(N=1;n=39)FVC (% Predicted)*C20 30 40 50 60 70 80 90 Out-patient(N=8;n=402) In-patient(N=8;n=215)FVC (% Predicted)*DRespiratory Research 2006, 7:74 http://respiratory-research.com/content/7/1/74Page 8 of 14(page number not for citation purposes)Fixed Effect Meta-Analysis Results of Selected Clinical Variablesigure 2Fixed Effect Meta-Analysis Results of Selected Clinical Variables. Graphs displayed are: A) FEV1/FVC Ratio (Exacerba-tion Severity Levels I to III); B) FEV1/FVC Ratio (Out- versus In-patient Setting); C) Pack Years (Levels I to III); and D) Pack Years (Out- versus In-patient Setting). For each clinical variable, the point estimates (point), 95% confidence intervals (box), and two standard deviations (bars) are presented for Levels I to III and out- & in-patient settings. 'N' signifies the total studies and 'n' is the total subjects. P < 0.017 is indicated for statistical comparisons of Level I versus II (*), II versus III (†), and I versus III (#) as well as P < 0.05 for comparison of out- versus in-patient setting (*).***20 40 60 80 100 Level I(N=7;n=541) Level II(N=10;n=388) Level III(N=1;n=39)FEV1/FVC (%)A20 40 60 80 100 Out-patient(N=7;n=541) In-patient(N=11;n=427)FEV1/FVC (%)*B0 20 40 60 80 100 120 Out-patient(N=43;n=13159) In-patient(N=26;n=2285)Pack YearsD0 20 40 60 80 100 120 Level I(N=43;n=13159) Level II(N=24;n=2187) Level III(N=2;n=98)Pack YearsCRespiratory Research 2006, 7:74 http://respiratory-research.com/content/7/1/74Page 9 of 14(page number not for citation purposes)Fixed Effect Meta-Analysis Results of Selected Clinical Variablesigure 3Fixed Effect Meta-Analysis Results of Selected Clinical Variables. Graphs displayed are: A) Heart Rate (Exacerbation Severity Levels I to III); B) Heart Rate (Out- versus In-patient Setting); C) Breathing Rate (Levels I to III); and D) Breathing Rate (Out- versus In-patient Setting). For each clinical variable, the point estimates (point), 95% confidence intervals (box), and two standard deviations (bars) are presented for Levels I to III and out- & in-patient settings. 'N' signifies the total studies and 'n' is the total subjects. P < 0.017 is indicated for statistical comparisons of Level I versus II (*), II versus III (†), and I versus III (#) as well as P < 0.05 for comparison of out- versus in-patient setting (*).†#**10 20 30 40 Level I(N=7;n=1213) Level II(N=8;n=620) Level III(N=27;n=1779)Breaths / MinuteC60 80 100 120 140 Out-patient(N=10;n=591) In-patient(N=25;n=1813)Heart Rate (bpm)*B60 80 100 120 140 Level I(N=10;n=591) Level II(N=7;n=329) Level III(N=18;n=1484)Heart Rate (bpm)*A10 20 30 40 Out-patient(N=7;n=1213) In-patient(N=35;n=2399)Breaths / MinuteDRespiratory Research 2006, 7:74 http://respiratory-research.com/content/7/1/74Page 10 of 14(page number not for citation purposes)Fixed Effect Meta-Analysis Results of Selected Clinical Variablesigure 4Fixed Effect Meta-Analysis Results of Selected Clinical Variables. Graphs displayed are: A) Arterial Carbon Dioxide Tension, PaCO2(Exacerbation Severity Levels I to III); B) PaCO2 (Out- versus In-patient Setting); C) Percent Oxygen Saturation – Arterial & Pulse Measurements Combined (Levels I to III); and D) Percent Oxygen Saturation – Arterial & Pulse Measure-ments Combined (Out- versus In-patient Setting). For each clinical variable, the point estimates (point), 95% confidence inter-vals (box), and two standard deviations (bars) are presented for Levels I to III and out- & in-patient settings. 'N' signifies the total studies and 'n' is the total subjects. P < 0.017 is indicated for statistical comparisons of Level I versus II (*), II versus III (†), and I versus III (#) as well as P < 0.05 for comparison of out- versus in-patient setting (*).70 80 90 100 110 Out-patient(N=7;n=428) In-patient(N=12;n=563)Oxygen Saturation (Arterial + Pulse) (%)*D20 30 40 50 60 70 80 90 Level I(N=6;n=343) Level II(N=45;n=4058) Level III(N=37;n=1710)PaCO2 (mmHg)†#*A70 80 90 100 110 Level I(N=7;n=428) Level II(N=5;n=403) Level III(N=7;n=160)Oxygen Saturation (Arterial + Pulse) (%)#*C20 30 40 50 60 70 80 90 Out-patient(N=6;n=343) In-patient(N=81;n=5768)PaCO2 (mmHg)*BRespiratory Research 2006, 7:74 http://respiratory-research.com/content/7/1/74study, COPD patients with 40 to 60 pack-years of smok-ing will experience an increase in the severity of COPDexacerbations. However, our conclusion regarding thisfinding is limited by there being data from only two stud-ies at Level III.Although heart rate varied little between ExacerbationLevels II to III, it is important to note that it was substan-tially elevated in patients (Figure 3A) with the clearest dif-ference being between in- and out-patients. This ispossibly associated with the anxiety and dyspnea thatexperienced when an exacerbation occurs. The increase inheart rate of course increases the oxygen requirements ofthe heart. The increased heart rate may also be the resultof underlying cardiovascular disease that is more promi-nent in severe COPD patients [43].The relationship of pH and bicarbonate to exacerbationseverity are consistent with the signs of respiratory acido-sis evident in COPD patients with exacerbations[1,24,25]. However, due to the shortage of data in Level I,proper statistical conclusions about each of these varia-bles are difficult to make. In relation to this, breathing ratesignificantly increased from Levels I to II and thendecreased from Levels II to III (Figure 3C). The first obser-vation may reflect components of the exacerbation epi-sode (i.e., anxiety and dyspnea) as well as thephysiological need to breathe more to maintain adequateblood gas levels. The reduction at Level III possibly reflectsthe results of the specialized care where patients are givenventilatory support so as to return the breathing rate tonormal. The Borg Dyspnea Score showed the same trendas breathing rate, although insufficient data in Level I didnot allow for further comparisons. When out- and in-patient data were compared for each of these variables,only breathing rate demonstrated a clear statistical differ-ence (Figure 3D). The Borg Dyspnoea Score on the otherhand did not have enough studies in the out-patient cate-gory to perform any statistical test. Overall, the observedtrends were consistent with the fact that management ofdyspnoea is one of the main factors generating the highhospital costs associated with COPD exacerbations [44].In keeping with the direct measures of dyspnoea, arterialcarbon dioxide tension showed a clear relationship withexacerbation severity and patient management settings(Figures 4A and 4B) that is consistent with the conclu-sions reported in the medical literature [20,45-47]. Arte-rial oxygen tension in contrast did not change withexacerbation severity or patient setting. Possibly this lackof correlation reflects the immediate administration ofsupplemental oxygen given to hypoxaemic patients in ahospital setting. There was however a decreasing trend inoxygen saturation with increasing exacerbation severity(Figures 4C and 4D) that are consistent with the presentthinking on blood gas changes.Most of the other commonly accepted measures and sug-gested biomarkers poorly reflected exacerbation severity,or the fact that there was not sufficient data to undertakea meta-analysis (See additional file 1). This finding recallsa 2001 US Department of Health and Human Servicesreport on exacerbation treatment outcomes from over 200randomised controlled trials [14]. The aim of that studywas to create new guidelines to improve the managementof COPD exacerbations. That study also concluded thatthe current literature was limited in terms of the numberof studies and the amount of detail available as well as thereliability and accuracy of the clinical assessments used todiscriminate between COPD exacerbations and othercauses of worsening respiratory status. Thus, our observa-tions agree with previous observations regarding theassessment of the unstable COPD literature.As previously discussed, most of the studies used for thisreview were predominately with hospitalized patients(Level II). However, most COPD occurs in an out-patientsetting (Level I) [48-53]. This has implications for ourstudy since the latter population was poorly represented.Our basic categorisation was according to the ATS/ERS'operational scheme for classifying the severity of COPDexacerbations as well as to out- and in-patient categories.To our knowledge, we are the first to undertake this typeof literature review and thus we were faced with a lack ofconsistency in the definition of exacerbations as used inthe various studies. We tried to overcome this difficulty byselecting and ranking clinical studies so as to improve thecomparability of subjects between studies.We were also aware that the clinical studies we analyseddiffered with respect to which comorbidities or identifia-ble causes for exacerbations were reported. Most patientswere elderly and therefore were more likely to be sufferingfrom one or more co-existing diseases such as asthma orcardiovascular disease. Such co-morbidity makes interpre-tation of our findings more difficult with respect to thetrue causes of exacerbations. If their aetiology could bedetermined, then susceptible patients such as those inLevel I could be identified and new treatments developedto help prevent their onset and related hospital costs.Finally, the compatibility between the studies of COPDexacerbation that we analysed may have been limited bysubstantial variations in the time and location of studies.Exacerbations are more likely in summer [5] but manystudies failed to report the time of year or the time periodPage 11 of 14(page number not for citation purposes)and clear differences between out- and in-patient settings for study implementation. Thus, seasonal effects, com-bined with the low incidence of exacerbations per patient,Respiratory Research 2006, 7:74 http://respiratory-research.com/content/7/1/74could represent an inherent bias. In addition, differentinstitutions probably had different standards with respectto diagnosis and management of COPD exacerbationswhen these studies were performed. Such variations mayalso explain any observed inconsistencies in our findings.However, we attempted to overcome this possible bias inExacerbation Levels II and III by the subsequent re-analy-sis of this data on the basis of out-patient and in-patientsettings.As observed in The additional online file, there was a scar-city of information particularly for biomarkers at differentexacerbation levels. It is also unclear to us whether any ofthe variables that changed with exacerbation severity arecausally-related. Hence, longitudinal studies and/or lessrestrictive eligibility criteria would be needed to addressall these questions. One difficulty in tackling such prob-lems is the enormous amount of time and expenseinvolved in implementing such studies. In addition, thecurrent methods for data analysis in clinical studies havelimitations imposed by the assessment of the reduction infrequency or total suppression of exacerbation episodes(i.e. rare event or "non-event").To overcome these drawbacks and obtain more accurateevaluation of treatment effect on COPD exacerbations,alternative analytical methods based, for example, on pre-dictive mathematical models such as hidden Markovchains or Bayesian forecasting should be tried. Such mod-els can characterise and predict rare events without under-taking a full-scale, long-term longitudinal study. Thisapproach to predicting rare events has been used previ-ously in studies of migraine, epilepsy and various cardio-vascular diseases where the size of treatment effect ismeasured in terms of a reduction in the frequency of therepetition of an event within a given probability or withina given time period [54,55]. One example of a mathemat-ical model development includes the use of a Markovmodel to predict COPD exacerbation rates in a clinicaltrial of the inhaled anticholinergic bronchodilator tiotro-pium [56]. In this example, the model was developed onthe basis of prior knowledge of the exacerbation rate asestimated from meta-analyses of randomised controlledtrial data. This gave the probabilities for COPD exacerba-tions for different stages of COPD. In another study, a pro-portional hazards model was used to identify risk factorsfor COPD patients hospitalised due to an exacerbation[44]. The current ATS/ERS guidelines for exacerbations donot consider the implications of using probabilistic mod-els as a means of assessing the severity of COPD exacerba-tions or the effect of treatment [1]. A modelling approachmay offer new insights into which variables related toCOPD exacerbations should be investigated.From a research planning perspective, our study findingshave generated some hypotheses and related considera-tions that could be evaluated in future clinical trials. Onehypothesis is that the combination of variables that weobserved to change in our study (i.e., FEV1, FVC, FEV1/FVC, arterial carbon dioxide, breathing rate, heart rate,pack years, and oxygen saturation) could represent a newdefinition for a 'severe' exacerbation event. Most defini-tions in the literature, including the recent ATS/ERS defi-nition, do not indicate any assessment of(patho)physiological variables as signs of an exacerba-tion. They simply regard the exacerbation as a worseningof the normal day-to-day symptoms and/or an adjust-ment in medical management [17]. A definition thatencompasses a clear set of objective measures would beuseful to medical practitioners who predominantly relyon clinical judgement or past experiences for diagnosingan exacerbation and its severity as well as for assessingtreatment effect.Another important consideration for future clinical trialsis the assessment of treatment effect based on predictionsof exacerbation frequency and intensity. In other words,the collection of data such as the rate of onset and resolu-tion of an exacerbation from longitudinal studies couldbe used to determine probabilities of second, third,fourth, etc., exacerbation events in individual patients[54]. The alteration of such probabilities with an experi-mental treatment could be a more sensitive and reliableapproach for assessing treatment effect in clinical trialsthan recording daily changes in symptoms or medicalmanagement.Lastly, our findings were obtained from COPD patientsthat had experienced at least one exacerbation during thestudy assessment period. In the same studies, there werealso patients who did not experience an exacerbation. Thisindicates that a fraction of COPD patients may beregarded as being susceptible to an exacerbation whereasanother fraction is 'exacerbation-free'. It would be inter-esting to determine how the variables we identified in ourstudy change in the latter patient group according to FEV1.Some published studies have stratified COPD patients onthe basis of exacerbation frequency; this is generally doneby categorising patients as having either 'infrequent' or'frequent' exacerbations if they had less than or greaterthan a mean of three exacerbations per year, respectively[57]. In our study, we were unable to make this distinctionbetween COPD patients since many of the publishedstudies did not provide individual patient data on exacer-bation frequency. We are currently investigating a com-mercial database of clinical trials that will enable us tolook at patients with 'infrequent' or 'frequent' exacerba-Page 12 of 14(page number not for citation purposes)tions. The results of this work could help us better selectRespiratory Research 2006, 7:74 http://respiratory-research.com/content/7/1/74patients as well as identify potential markers for futurelongitudinal studies.ConclusionThe current management and treatment of COPD exacer-bations is primarily dependent on the evaluation of thesymptoms rather than the signs related to the exacerba-tion event. We found that arterial carbon dioxide tensionand breathing rate consistently varied with the severity ofCOPD exacerbations and with in- versus out-patients.Other commonly-accepted measures and suggestedbiomarkers for exacerbations failed to show consistenttrends or lacked sufficient data to permit any meta-analy-sis. We recommend the design of longitudinal studieslooking at the frequency of exacerbations as well as theuse of more advanced modelling techniques to improvethe selection of potential markers for the categorization ofthe severity of COPD exacerbations and the assessment oftreatment effect in future studies.AbbreviationsATS – American Thoracic SocietyERS – European Respiratory SocietyCOPD – Chronic Obstructive Pulmonary DiseaseFEV1 – Forced Expired Volume in One SecondFVC – Forced Vital CapacityCompeting interestsThe author(s) declare that they have no competing inter-ests.Authors' contributionsLF and ODP contributed to the research concept. LF per-formed the data collection, abstraction and analysis. Allauthors contributed to data interpretation. LF wrote thefirst draft of the manuscript and all authors took part inthe revision and final version of this report.Additional materialsite containing the study references for this work. The current research is part of L. Franciosi's post-doctoral fellowship on COPD disease progres-sion funded by GlaxoSmithKline UK.References1. Celli BR, MacNee W: Standards for the diagnosis and treat-ment of patients with COPD: a summary of the ATS/ERSposition paper.  Eur Respir J 2004, 23:932-946.2. Wedzicha JA, Donaldson GC: Exacerbations of chronic obstruc-tive pulmonary disease.  Respir Care 2003, 48:1204-1213.3. Seemungal TA, Donaldson GC, Paul EA, Bestall JC, Jeffries DJ, Wed-zicha JA: Effect of exacerbation on quality of life in patientswith chronic obstructive pulmonary disease.  Am J Respir CritCare Med 1998, 157:1418-1422.4. Anthonisen NR, Manfreda J, Warren CP, Hershfield ES, Harding GK,Nelson NA: Antibiotic therapy in exacerbations of chronicobstructive pulmonary disease.  Ann Intern Med 1987,106:196-204.5. Donaldson GC, Seemungal T, Jeffries DJ, Wedzicha JA: Effect oftemperature on lung function and symptoms in chronicobstructive pulmonary disease.  Eur Respir J 1999, 13:844-849.6. 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Lifetime Data Anal 1997, 3:315-335.56. Oostenbrink JB, Rutten-van Molken MP, Monz BU, FitzGerald JM:Probabilistic Markov model to assess the cost-effectivenessof bronchodilator therapy in COPD patients in differentcountries.  Value Health 2005, 8:32-46.57. Donaldson GC, Seemungal TA, Bhowmik A, Wedzicha JA: Relation-ship between exacerbation frequency and lung functiondecline in chronic obstructive pulmonary disease.  Thorax2002, 57:847-852.yours — you keep the copyrightSubmit your manuscript here:http://www.biomedcentral.com/info/publishing_adv.aspBioMedcentralPage 14 of 14(page number not for citation purposes)Am J Respir Crit Care Med 2001, 164:1002-1007.

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