UBC Faculty Research and Publications

Myocardial Infarction Injury in Patients with Chronic Lung Disease Entering Pulmonary Rehabilitation… Lau, Benny C.; Taylor, Carolyn M.; Eeden van, Stephan F.; Camp, Patricia G.; Sima, Carmen Aurelia; Reid, Wendy Darlene; Sheel, Andrew William; Kirkham, Ashley Jul 19, 2017

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0   1 Myocardial Infarction Injury in Patients with Chronic Lung Disease Entering  2 Pulmonary Rehabilitation: Frequency and Association with Heart Rate Parameters  3        4        5        6        7        8  9  10  11  12  13  14  15  16  17  18  19  20  21  22 Carmen A. Sima, Benny C. Lau, Carolyn M. Taylor, Stephan F. van Eeden, W. Darlene Reid, Andrew W. Sheel, Ashley R. Kirkham, Pat. G. Camp  Submitted 19 July 2017  1   23 ABSTRACT  24 Background: Myocardial infarction (MI) remains under-recognized in chronic lung disease  25 (CLD) patients. Rehabilitation health professionals need accessible clinical measurements  26 to identify the presence of prior MI in order to determine appropriate training prescription.  27 Objectives: We aimed to estimate prior MI in CLD patients entering a pulmonary  28 rehabilitation program, as well as its association with heart rate parameters such as resting  29 heart rate and chronotropic response index.  30 Design: Retrospective cohort design.  31 Setting: Pulmonary rehabilitation outpatient clinic in a tertiary care university-affiliated  32 hospital.  33 Patients: Eighty-five CLD patients were studied.  34 Methods: Electrocardiograms at rest and peak cardiopulmonary exercise testing, performed  35 before pulmonary rehabilitation, were analyzed. Electrocardiographic evidence of prior MI,  36 quantified by the cardiac infarction injury score (CIIS), was contrasted with reported  37 myocardial events and then correlated with resting heart rate and chronotropic response  38 index parameters.  39 Main outcome measurements: Cardiac infarction injury score, resting heart rate and  40 chronotropic response index.  41 Results: Sixteen CLD patients (19%) demonstrated electrocardiographic evidence of prior  42 MI, but less than half (8%) had a reported MI history (p <.05). The Cohen’s Kappa test  43 revealed poor level of agreement between CIIS and medical records (kappa = 0.165),  44 indicating that prior MI diagnosis was under-reported in the medical records. Simple and 2   45 multiple regression analyses showed that resting heart rate but not chronotropic response  46 index was positively associated with CIIS in our population (R2  = 0.29, p <.001). CLD  47 patients with a resting heart rate over 80 beats/min had approximately 5 times higher odds  48 of having prior MI, as evidenced by a CIIS > 20.  49 Conclusions: CLD patients entering pulmonary rehabilitation are at risk of unreported prior  50 MI. Elevated resting heart rate seems to be an indicator of prior MI in CLD patients;  51 therefore, careful adjustment of training intensity such as intermittent training is  52 recommended under these circumstances.  53 Level of evidence: III  54  55  56  57  58  59  60  61  62  63  64  65 Keywords: chronic lung disease; pulmonary rehabilitation; myocardial infarction; cardiac  66 infarction injury score; heart rate; chronotropic incompetence. 3   67 INTRODUCTION  68 Ischemic heart disease is a major determinant of morbidity and mortality among  69 individuals with chronic lung diseases (CLD), particularly those with chronic obstructive  70 pulmonary disease (COPD) [1,2]. Moreover, myocardial infarction (MI), which is a serious  71 manifestation of ischemic heart disease, remains commonly under-recognized in this  72 population [3,4]. Given that survivors of MI are at high risk of poor outcomes and future  73 cardiac events (with a relative risk of recurrent MI and cardiovascular mortality increased  74 by more than 30% compared to general population) [5], overlooking this condition in CLD  75 patients can lead to inadequate treatment decisions. This aspect is particularly relevant in a  76 pulmonary rehabilitation setting where health care professionals should be aware of prior  77 MI to determine appropriate training prescription and avoid adverse cardiac events  78 associated with exercise such as arrhythmia, recurrent myocardial ischemia, or infarction  79 [6,7].  80 Pulmonary rehabilitation is an evidence-based intervention that combines exercise  81 training and education to improve physical condition and health related quality of life of  82 patients with CLD [8]. Before starting a pulmonary rehabilitation program (PRP), patients  83 with CLD undergo a health history to identify those at high risk for complications that may  84 emerge during exercise training [8]. However, the history of comorbidities often relies on  85 patients’ self-report rather than objective medical assessments. Exercise tests are also  86 performed to evaluate patients’ exercise tolerance and prescribe exercise intensity [9].  87 Nevertheless, while symptom-limited incremental exercise tests, such as a cardiopulmonary  88 exercise test (CPET), are useful for identifying myocardial ischemic injury, they are not 4   89 always available or routinely performed before pulmonary rehabilitation. With these  90 limitations being recognized [10,11], rehabilitation health professionals must rely on other  91 accessible clinical measurements to estimate the presence of prior MI.  92 A number of electrocardiographic (ECG) classification systems are currently available  93 to estimate the presence and/or severity of prior MI. The Cardiac Infarction Injury Score  94 (CIIS), which is a validated ECG score [12], has been shown to be highly accurate at  95 detecting prior MI. Whether used as a categorical or continuous variable, the CIIS can  96 provide useful information on myocardial damage and cardiac events [13]. Furthermore, a  97 CIIS value equal or greater than 20 is a significant predictor of cardiovascular mortality in  98 apparently healthy middle-aged individuals [14] and patients with COPD [3,15]. Therefore,  99 the CIIS is a convenient, non-invasive diagnostic tool to detect prior MI.  100 Resting heart rate and heart rate response to exercise are two hemodynamic parameters  101 regularly monitored in the rehabilitation setting, which also carry prognostic information  102 about cardiac ischemic risk [16,17]. A persistently elevated resting heart rate has been  103 shown to be involved in the pathophysiology of atherosclerosis [18] and acute coronary  104 events [19]. In particular, resting heart rates over 80 beats/minute have been associated with  105 increased risk of all-cause and cardiovascular mortality in both general and high-risk  106 populations [20,21]. An inadequate heart rate increase in response to exercise (e.g.,  107 chronotropic incompetence) has been also found correlated with the incidence of coronary  108 disease and the risk of cardiovascular death [22,23]. Despite patients with CLD commonly  109 displaying both elevated resting heart rate and chronotropic incompetence [24-26], there is 5   110 no study to date investigating the relationship between these two parameters and prior MI  111 in this population.  112 We conducted a retrospective chart and a database review to estimate the presence of  113 prior MI in CLD patients entering a PRP based on their CIIS, and to determine if a MI was  114 reported in the medical records. Secondly, we evaluated whether resting heart rate and  115 chronotropic response are associated with prior MI, as assessed by the CIIS, in this CLD  116 population. Our hypothesis was that the frequency of prior MI quantified through the CIIS  117 would be higher than that reported in the medical records, and a positive association  118 between heart rate parameters and CIIS would be present in this population. Because CLD  119 patients are a heterogeneous group, we also determined if the results differed in patients  120 diagnosed with COPD compared to patients diagnosed with other CLD.  121  122 METHODS  123 Study design and population  124 This study used a retrospective cohort design and was conducted in a pulmonary  125 rehabilitation outpatient clinic in a tertiary care university-affiliated hospital. The medical  126 records of CLD patients referred for a PRP between January 2010 and December 2014  127 were reviewed. Data was collected from the patients who met the following inclusion  128 criteria: over 35 years of age; a physician diagnosis of CLD confirmed by clinical,  129 radiological, and pulmonary function examinations; an available symptom-limited  130 cardiopulmonary exercise testing (CPET) performed on an electronic cycle ergometer using  131 an individualized ramp protocol with 5 or 10 watts per minute increments, according to 6   132 published guidelines [27], before the start of the PRP; and twelve-lead ECG recordings  133 obtained at rest and during the CPET. Patients were excluded if they had: uninterpretable or  134 irretrievable ECGs; missing hemodynamic data at resting and peak exercise; or conditions  135 altering CIIS calculation such as atrial fibrillation, ventricular paced rhythm, left bundle  136 branch block, and left ventricular hypertrophy with repolarization abnormalities. For  137 patients with more than one admission to PRP during the inclusion period, data collected  138 from the latest admission was used. Ethical approval to conduct the study was obtained  139 from the appropriate Research Ethics Board.  140  141 Study procedure  142 Two sources of data consisting of the patients’ medical record and PRP database  143 contributed to the retrospective data collection. First, each patient’s medical record was  144 electronically searched in order to retrieve information on the completion of a CPET before  145 entering PRP and standard 12-lead ECGs recorded at rest and during the CPET. Next, the  146 PRP database and CPET electronic records were reviewed to collect patients’  147 characteristics, medical history, and hemodynamic and functional measurements.  148  149 Electrocardiographic classification of prior myocardial infarction  150 To estimate the presence of prior myocardial events, the CIIS was calculated from the  151 baseline ECGs obtained at rest, before commencing the CPET. A cardiologist and a trained  152 health professional with expertise in electrocardiography, blind to any patient information,  153 independently analyzed each ECG for recording accuracy. Twelve specific ECG features 7   154 including R, S and T wave amplitudes, Q wave duration, and Q/R amplitude ratios were  155 measured, tabulated, and converted to a CIIS [12]. To avoid any interpretation errors in this  156 process, a calculation protocol was developed a priori and refined until the inter-rater  157 reliability exceeded 0.90. Any disagreements between the two assessors were resolved  158 through discussion. Patients were classified as having prior MI if their CIIS was equal to or  159 greater than 20, as this value accurately classifies a “probable infarction” in an adult  160 population [12,28].  161  162 Heart rate measurements  163 Resting and peak heart rate were collected as values measured at rest prior to CPET and  164 during the last minute of CPET, respectively. Chronotropic response index (CRI), which  165 represents the capacity to increase the heart rate in response to exercise, was calculated as  166 the percentage of heart rate reserve that was used during exercise: [(peak heart rate –  167 resting heart rate) x 100/(220-age) – (resting heart rate)] [29]. A cut-off point of ≤ 80% was  168 considered as chronotropic incompetence [23], except for subjects on β-blockers where a  169 cut-off point of < 62% was applied [30]. Based on the CPET records, all patients took their  170 medications including inhalers on the morning of the test.  171  172 Additional clinical outcomes  173 Spirometric measurements [percent predicted forced expiratory volume in 1 second  174 (FEV1), forced vital capacity (FVC), and FEV1/FVC ratio] were gathered from patient  175 records along with age, height, weight, smoking status, and use of oxygen. Body mass 8   176 index (BMI) was calculated as weight divided by height squared. Indices of submaximal  177 [e.g., distance walked during a six-minute walk test (6MWD)] and maximal/peak exercise  178 capacity [e.g., oxygen uptake (VO2), workload, and exercise time] were also collected  179 along with information on medications and comorbidities. Both the 6MWD and the  180 progressive incremental cycle ergometry CPET protocols were performed in the clinical  181 setting following the standard guidelines [27,31]. Given that our data was collected from  182 CLD patients before they commenced the pulmonary rehabilitation program, no description  183 of the content of exercise training program is provided in the present manuscript. All  184 comorbidities, including MI, were defined on the basis of self-report or physician reports.  185  186 Statistical analysis  187 For descriptive statistics, continuous variables were described using means and standard  188 deviations, whereas categorical data were described using counts and percentages.  189 Differences in patients’ baseline characteristics according to the patient groups (COPD  190 versus non-COPD) were compared using parametric (Student’s t-test) or non-parametric  191 (Wilcoxon Mann-Whitney) tests for continuous variables, and Chi-square or Fisher’s tests  192 for categorical variables. The Cohen’s Kappa test was used to compare the agreement  193 between CIIS and medical records of past myocardial events. Univariate correlations and  194 multivariate regression analyses were performed to assess the relationship between CIIS  195 and heart rate parameters in our CLD population, considering CIIS first as a continuous  196 variable, then as a dichotomous variable (CIIS ≥ 20 versus CIIS < 20). Resting heart rate  197 and chronotropic response index were also included in the analysis as continuous and 9   198 categorical variables. Stepwise regression was applied to select suitable variables for use in  199 the regression model. All statistical analyses were performed using the statistical software  200 package SAS for Windows, version 9.4 (SAS Institute, Cary, North Carolina). A p value <  201 .05 was considered statistically significant.  202  203 RESULTS  204 Population sample  205 In the considered time frame, one hundred and sixteen CLD patients with CPET were  206 identified. Of the 116 potential participants, 31 patients (27%) were excluded because they  207 either had uninterpretable or missing ECGs, pharmacological or treadmill stress testing, or  208 conditions known to alter CIIS interpretation. Therefore, 85 chronic lung disease patients  209 were included in the final analysis of whom 54 patients had a physician diagnosis of COPD  210 (COPD group) and 31 patients had a physician diagnosis of CLD other than COPD (non-  211 COPD group). Diagnoses in the non-COPD group included bronchiectasis (n=1), chronic  212 asthma (n=2), cystic fibrosis (n=2), combined obstructive-restrictive patterns  213 (FEV1/FVC>70) (n=10), and interstitial lung diseases such as sarcoidosis, nonspecific  214 interstitial pneumonia, idiopathic pulmonary fibrosis, and hypersensitivity pneumonitis  215 (n=16). The study flow diagram is presented in Figure 1.  216  217 Participant characteristics  218 The study population had a mean age (± SD) of 64 ± 10 years and 52% were male. The  219 COPD and non-COPD groups did not differ significantly in patient characteristics except 10   220 for sex, smoking status, pulmonary function tests, and pulmonary medication prescription  221 (Table 1). While the individuals in the COPD group were predominantly men (61%) with  222 moderate-severe pulmonary obstruction (FEV1 50 ± 17% predicted; FEV1/FVC 48 ± 12),  223 the individuals in the non-COPD group were predominantly women (65%) with mild-  224 moderate pulmonary restriction (FVC 73 ± 14% predicted; FEV1/FVC 77 ± 12), and fewer  225 pack-years. The COPD patients used significantly more lung medications than those in the  226 non-COPD group, but no differences between the two groups were found in the use of  227 cardiovascular medications. Renin-angiotensin system (RAS) antagonists were the most  228 frequent, and beta-blockers the least frequent, cardiovascular medications prescribed in this  229 population. Ischemic heart disease, hypertension, and dysrhythmias were the main  230 cardiovascular diseases found in the patients’ medical records.  231  232 Myocardial infarction history  233 Sixteen CLD patients (19%) were classified as having prior MI based on a CIIS ≥ 20,  234 compared to only seven patients (8%) who had reported acute myocardial events according  235 to their medical records (p = .03). The Cohen’s Kappa test revealed poor level of agreement  236 between CIIS and medical records (kappa = 0.165). This means that a significant  237 percentage of patients with prior MI were detected only through CIIS, indicating that prior  238 MI diagnosis was under-reported in the medical records. The percentages of patients with  239 prior MI evidenced by CIIS ≥ 20 and medical records were similar in the COPD group  240 (17% versus 11%, p = .37), but differed significantly in the non-COPD group (23% versus  241 3%, p = .02), as illustrated in Figure 2. 11   242 Relationship between CIIS and heart rate variables  243 Hemodynamic and functional capacity data are presented in Table 2. On average, the  244 study population had a CIIS of 13.0 ± 8.1 with similar (non-significant differences) values  245 in the COPD group (13.2 ± 6.8) and the non-COPD group (12.5 ± 10.1). While resting  246 heart rate did not differ between the two groups, the COPD group manifested significantly  247 lower peak heart rate and percent predicted heart rate (121 ± 18 beats/min and 78 ± 12%,  248 respectively) compared to the non-COPD group (138 ± 19 beats/min and 87 ± 11%,  249 respectively). The COPD group also had significantly lower chronotropic response (e.g.,  250 CRI 53 ± 22% versus 74 ± 21%), submaximal (6MWD 385 ± 106 meters versus 438 ± 92  251 meters) and maximal functional exercise capacity indices (e.g., relative peak VO2 16.6 ±  252 4.9 mL/kg/min versus 19.1 ± 4.5 mL/kg/min) compared to the non-COPD group.  253 Univariate correlations, employed to determine heart rate parameters significantly  254 associated with CIIS, considered as a continuous variable, showed that resting heart rate  255 (r=0.22, p = .04), but not chronotropic response index (r=0.12, p = .27) was positively  256 associated with CIIS. Multivariate regression analyses indicated that resting heart rate  257 remained significantly associated with CIIS even after adjusting for confounding factors  258 such as diastolic blood pressure, FVC, and the use of cardiovascular medication  259 (particularly the absence of RAS antagonist prescription) (R2=0.29, p < .001). As illustrated  260 in Table 3, these results were similar (R2=0.27, p < .001) when resting heart rate was  261 expressed as a dichotomous variable (HR>80 beats/min).  262 When CIIS was considered as a dichotomous variable (CIIS ≥ 20 versus CIIS < 20), the  263 logistic regression indicated that the resting heart rate was a significant predictor of CIIS (p 12   264 = .04) only when resting heart rate was used as a dichotomous variable; patients with a  265 resting heart rate over 80 beats/min had approximately 5 times higher odds of having a  266 CIIS > 20. In the same analysis the absence of RAS antagonist medication, but not diastolic  267 blood pressure or FVC, reached significance (Table 4). The inclusion of the CLD diagnosis  268 (COPD or non-COPD) as an independent variable did not improve any of the regression  269 models.  270  271 DISCUSSION  272 We found that CLD patients entering pulmonary rehabilitation were at risk of  273 unreported prior MI. Although the proportion of prior MI, as detected by the CIIS score,  274 was similar in COPD and non-COPD patient groups, the COPD patients were more likely  275 to have a reported MI in their medical history. In addition, resting heart rate, but not  276 chronotropic response index, was significantly associated with CIIS in this CLD  277 population. An elevated resting heart rate (e.g., over 80 beats/min) was found to be an  278 indicator of prior MI in CLD patients, and therefore, it raises awareness for careful  279 adjustments of training intensity under these circumstances.  280 Previous studies that investigated MI history in patients with COPD using ECG  281 classification schemes reported frequency values ranging around 20%. Vanfleteren et al.  282 [4], using the Minnesota scoring system, found that 21% of COPD patients entering a PRP  283 presented ECG changes suggestive of silent MI, and 14% of these patients did not have any  284 medical records of ischemic heart disease. With a CIIS cut-off value of 20, Sillen et al. [32]  285 showed that approximately 10% of the COPD patients in Global Initiative for Chronic 13   286 Obstructive Lung Disease (GOLD)-D stage referred to PRP had prior MI. Similarly, Karoli  287 et al. [15] found that 12.1% and 5.6% of the COPD patients in their study had a prior MI  288 according to the ECG and medical records, respectively. Moreover, they found that a CIIS  289 above 20 represented a risk factor for death in this population.  290 Although the prevalence values may vary with the population or the diagnosis method,  291 our results are in line with these studies and show that 19% and 8% of CLD patients  292 enrolled in the PRP had a prior MI according to the ECG and medical records, respectively.  293 In addition, we found that the non-COPD patients were less likely to have a reported MI in  294 their history compared to the COPD patients. Therefore, these results show the importance  295 of screening for ischemic heart disease in all patients with CLD entering pulmonary  296 rehabilitation.  297 We also found that CLD patients entering our PRP displayed elevated resting heart rate  298 with values being about 20 beats/min higher than those reported in the literature for  299 apparently healthy individuals of the same age [33]. Moreover, the resting heart rate in our  300 CLD population was on average 85 beats/min, a value that has been shown to be associated  301 with increased risk of all-cause and cardiovascular mortality in both general [20,21] and  302 COPD [34] populations.  303 Despite similar resting heart rate values, we found that the COPD group displayed  304 significantly lower heart rate values at peak exercise than the non-COPD group. This  305 hemodynamic feature, paralleled by significant lower submaximal and maximal functional  306 capacities, can be explained by the higher pulmonary function impairment in the COPD  307 group compared to the non-COPD group. Nevertheless, both COPD and non-COPD 14   308 patients in our study showed limited capacity to increase their heart rate in response to  309 exercise, as evidenced by the presence of impaired chronotropic response in more than  310 three-quarters of all CLD patients. These results reinforce the opinion that in addition to  311 ventilatory limitation, which is recognized as a primary determinant of exercise tolerance  312 [35], the hemodynamic limitations, which have also been reported as exercise tolerance  313 predictors [36], should be taken into consideration in this population.  314 Finally, our results indicated that higher resting heart rate along with lower resting  315 diastolic blood pressure, higher FVC, and absence of RAS antagonist medication were  316 significantly associated with the CIIS in our CLD population. While the relationship  317 between elevated resting heart rate and cardiovascular ischemic risk is clearly established  318 [16,21], there are also studies that have reported an association between low diastolic blood  319 pressure and increased risk of MI in elderly people [37,38]. Our data also indicated that in  320 the absence of RAS antagonist medication, CLD patients were more likely to have had a  321 past myocardial event. These findings are in agreement with studies reporting that RAS  322 antagonists (particularly, angiotensin-converting enzyme inhibitors) have an important role  323 in the management of patients at increased cardiovascular risk by reducing MI, stroke, and  324 new-onset congestive heart failure [39]. Similar to other investigators [3], we were not able  325 to confirm the association between FEV1 and CIIS; however, we found that FVC was one  326 of the parameters of the model.  327 In summary, the weak but statistically significant association between resting heart rate  328 and CIIS found in this study cannot be excluded from consideration due to the magnitude  329 of risk associated with MI history. Moreover, elevated resting heart rate (e.g., over 80 15   330 beats/min) seems to be an indicator of prior MI in CLD patients, and therefore, a number of  331 training guiding principles can be applied under these circumstances. Based on the  332 literature addressing models of pulmonary rehabilitation for cardiovascular diseases  333 [40,41], starting a light-to-moderate exercise intensity (40-60% peak VO2) with a focus on  334 endurance is recommended in this population. After a duration of 20-30 minutes of aerobic  335 exercise is achieved, the intensity can be gradually increased to moderate-to-high levels  336 (60-80% peak VO2). Interval training can be also applied, in which moderate exercise  337 intensity of 0.5 - 4 seconds alternates with resting periods of 2 - 4 seconds. Finally,  338 providing oxygen supplementation during endurance training as well as reducing strength  339 training could prevent any further myocardial injury.  340 A number of limitations need to be considered in the interpretation of these results.  341 First, the study had a retrospective design, which might have introduced bias related to  342 accuracy and completeness of data from the medical records. Moreover, we excluded  343 patients with ventricular paced rhythm, left bundle branch block, and left ventricular  344 hypertrophy with repolarization abnormalities, that are known to alter the CIIS  345 interpretation. Since these conditions commonly co-exist with ischemic heart disease, our  346 findings might actually underestimate the real proportion of myocardial injury or infarction  347 in this population. Other limitations of our study could be related to the nature of the ECG  348 recordings. Some resting ECG recordings may have been performed with the patients in a  349 sitting position instead of supine, which could have introduced motion artifacts that could  350 alter the CIIS calculation. However, our total CIIS (13.0 ± 8.1) was similar to Brekke et al.  351 study (13.5 ± 11.6), which was performed supine in a population of patients with acute 16   352 exacerbation of COPD [3], giving us confidence that the patients’ position did not  353 significantly alter the CIIS. Since the resting heart rate values were measured before the  354 CPET, one could infer that neural impulses from the central command in anticipation of the  355 onset of exercise, use of inhaled bronchodilators (e.g., beta-adrenergic agonists), and/or  356 specific disease conditions (e.g., hypoxemia, dyspnea) could have lowered the accuracy of  357 data. However, the strength of this study is represented by the fact that even in the presence  358 of these potential influencing factors, we were able to detect a clinically relevant  359 association between elevated resting heart and prior MI in patients with CLD, and provide  360 physiotherapists with a resting heart rate threshold (e.g., 80 beats/min) that would enable  361 them to make informed and safe clinical decisions.  362  363 CONCLUSIONS  364 The present study showed that patients with chronic lung disease entering pulmonary  365 rehabilitation are at risk of unreported prior myocardial infarction. 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Does the relation of blood pressure to  477 coronary heart disease risk change with aging? The Framingham Heart Study. Circulation  478 2001;103(9):1245-1249. 22   479 (39) Latini R, Maggioni AP, Flather M, Sleight P, Tognoni G. ACE inhibitor use in patients  480 with myocardial infarction. Summary of evidence from clinical trials. Circulation  481 1995;92(10):3132-3137.  482 (40) Evans RA. Developing the model of pulmonary rehabilitation for chronic heart failure.  483 Chronic Respir Dis 2011;8(4):259-269.  484 (41) Troosters T, Van Remoortel H. Pulmonary rehabilitation and cardiovascular disease.  485 Semin Respir Crit Care Med 2009;30(6):675-683.  486  487  488  489  490  491  492  493  494  495  496  497  498  499  500 23   501 Table 1. Characteristics of the study participants   Variables Total  (n=85) COPD  (n=54) Non-COPD  (n=31) p  value Age (years) 64 ± 10 65 ± 8 62 ± 13 .19 Male/female (%) 52/48 61/39 35/65 .02 BMI (kg/m2) 27.3 ± 6.4 26.4 ± 6.4 28.7 ± 6.3 .08 Smoking history (pack-year) 34 ± 26 44 ± 23 17 ± 22 <.001 Current smokers, n (%) 16 (19) 14 (26) 2 (6) .04 Pulmonary function test     FEV1 (% predicted) 57 ± 19 50 ± 17 70 ± 15 <.001 FVC (% predicted) 77 ± 17 79 ± 18 73 ± 14 .07 FEV1/FVC 59 ± 19 48 ± 12 77 ± 12 <.001 Long-term oxygen therapy, n (%) 8 (9) 7 (13) 1 (3) .24 Lung medications     Number of lung medications 3 ± 2 4 ± 2 2 ± 2 .002 Short/long muscarinic antagonists, n (%) 43 (51) 34 (63) 9 (29) .003 Short/long beta agonists, n (%) 61 (72) 46 (85) 15 (48) <.001 Inhaled/oral corticosteroids, n (%) 56 (66) 36 (67) 20 (65) .84 Cardiovascular medications     Number of medications 1 ± 2 1 ± 2 1 ± 2 .98 RAS antagonists, n (%) 29 (34) 18 (33) 11 (35) .84 Anticoagulants, n (%) 19 (22) 12 (22) 7 (23) .97 24   Diuretics, n (%) 17 (20) 11 (20) 6 (19) .91 Statins, n (%) 15 (18) 9 (17) 6 (19) .75 Calcium antagonists, n (%) 14 (16) 9 (17) 5 (16) .94 Beta-blockers, n (%) 9 (11) 6 (11) 3 (10) >.99 Cardiovascular comorbidities     Ischemic heart disease, n (%) 29 (34) 18 (33) 11 (35) .84 Hypertension, n (%) 27 (32) 14 (26) 13 (42) .12 Dysrhythmias, n (%) 24 (28) 18 (33) 6 (19) .16 Legend: BMI = body mass index, FEV1 = forced expiratory volume in one second, FVC = forced vital capacity, RAS = renin angiotensin system; Values are described as mean ± standard deviation, except for sex, smoking status, medication, and comorbidities, which are described as counts and percentage; p < .05 significantly different between COPD and non-COPD patients   502  503  504  505  506  507  508  509  510  511  512 25   513 Table 2. Hemodynamic and functional capacity variables   Variables Total  (n=85) COPD  (n=54) Non-COPD  (n=31) p  value Cardiac infarction injury score 13.0 ± 8.1 13.2 ± 6.8 12.5 ± 10.1 .75 Resting HR (bpm) 85 ± 13 85 ± 14 85 ± 11 .80 Resting HR > 80, n (%) 55 (65) 33 (61) 22 (71) .36 Resting SBP (mmHg) 128 ± 20 127 ± 20 128 ± 22 .83 Resting DBP (mmHg) 78 ± 12 78 ± 13 77 ± 12 .83 Resting SpO2 (%) 97 ± 2 96 ± 2 97 ± 3 .01 Peak HR (bpm) 127 ± 20 121 ± 18 138 ± 19 <.001 Peak HR (% predicted) 81 ± 12 78 ± 12 87 ± 11 <.001 Peak SBP (mmHg) 176 ± 25 175 ± 26 179 ± 23 .45 Peak DBP (mmHg) 85 ± 13 85 ± 14 84 ± 12 .69 Relative Peak VO2 (mL/kg/min) 17.5 ± 4.9 16.6 ± 4.9 19.1 ± 4.5 .02 Relative Peak VO2 (% predicted) 72 ± 20 70 ± 20 77 ± 20 .09 Peak workload (Watts) 71 ± 27 68 ± 29 78 ± 23 .04 Exercise time (min) 6 ± 3 6 ± 3 7 ± 2 .03 CRI (%) 60 ± 24 53 ± 22 74 ± 21 <.001 CRI < 80, n (%) 67 (79) 47 (87) 20 (65) .01 6 MWD (meters) 405 ± 104 385 ± 106 438 ± 92 .04 26    Legend: HR = heart rate, bpm = beats/min, SBP = systolic blood pressure, DBP = diastolic blood pressure, SpO2 = blood oxygen saturation, VO2 = oxygen uptake, CRI = chronotropic response index, 6MWD = six minute walk distance test; Values are described as mean ± standard deviation, except for CRI, which is described as counts and percentage; p < .05 significantly different between COPD and non-COPD patients 514  515  516  517  518  519  520  521  522  523  524  525  526  527  528  529  530  531  532 27   533 Table 3. Multiple regression analysis for cardiac infarction injury score as continuous  534 variable  Independent variables β 95% CI p value Model 1    Resting HR (bpm) 0.17 (0.05, 0.28) .004 Resting DBP (mmHg) -0.17 (-0.29, -0.04) .008 FVC (% predicted) 0.13 (0.04, 0.22) .005 RAS antagonists (0) 4.64 (1.53, 7.75) .003 R-square 0.29   Model 2    Resting HR > 80 (bpm) 3.92 (0.59, 7.25) .02 Resting DBP (mmHg) -0.16 (-0.29, -0.03) .01 FVC (% predicted) 0.14 (0.04, 0.23) .006 RAS antagonists (0) 4.44 (1.12, 7.76) .009 R-square 0.27   Legend: HR = heart rate, bpm = beats/min, DBP = diastolic blood pressure, FVC = forced vital capacity, RAS (0) = absence of RAS  antagonist prescriptions  535  536  537  538 28   539 Table 4. Logistic regression analysis for cardiac infarction injury score as categorical  540 variable    Independent variables   β  Wald  Chi-square  Point estimate 95% Wald confidence limits  p  value Model 1      Resting HR (bpm) 0.05 3.4 1.1 (0.99, 1.11) .06 Resting DBP (mmHg) -0.05 3.6 0.9 (0.90, 1.00) .05 FVC (% predicted) 0.03 2.3 1.0 (0.99, 1.07) .13 RAS antagonists (0) 2.29 4.3 9.8 (1.14, 85.03) .03 Model 2      Resting HR > 80 (bpm) 1.56 3.9 4.7 (1.01, 22.24) .04 Resting DBP (mmHg) -0.06 3.7 0.9 (0.89, 1.00) .05 FVC (% predicted) 0.03 2.7 1.0 (0.99, 1.07) .09 RAS antagonists (0) 2.20 4.1 9.2 (1.06, 76.08) .04 Legend: HR = heart rate, bpm = beats/min, DBP = diastolic blood pressure, FVC = forced vital capacity, RAS (0) = absence of RAS  antagonist prescriptions  541  542  543  544  545 29   546 Figure 1. Study flow diagram  547  548 Figure 2. Percentage of patients with myocardial infarction based on the medical records  549 (gray bars) and Cardiac Infarction Injury Score (black bars); all chronic lung disease (CLD)  550 patients; COPD; and non-COPD; * p < .05 

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