Multidisciplinary Cardiac Rehabilitation and Long-Term Prognosis in Patients With Heart Failure
What is New?
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In this retrospective multicenter study, we observed that patients who participated in cardiac rehabilitation (CR) have a significantly lower risk of all-cause mortality and heart failure (HF) rehospitalization.
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CR participation was associated with a favorable prognosis in HF with preserved ejection fraction and across frailty subgroups, groups in whom effectiveness is still questioned.
What are the Clinical Implications?
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These findings support a benefit of outpatient CR in HF with preserved ejection fraction and HF with frailty, with a possible impact on survival and HF hospitalization.
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This study also suggests that comprehensive interventions, including exercise and patient education, such as CR, are of great importance in patients with HF with preserved ejection fraction and HF with frailty, where few effective treatments exist.
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More widespread use of CR as standard treatment for HF would be beneficial.
Introduction
Comprehensive cardiac rehabilitation (CR) is a class IA recommendation in patients with heart failure (HF),1,2 as it improves functional capacity and quality of life (QoL)3,4 and reduces risk of readmission in patients with HF with reduced left ventricular ejection fraction (HFrEF).4,5
Recent meta-analyses showed that exercise-based CR improved QoL and exercise capacity in patients with HF.3,4 Further studies are required as the efficacy of CR in preventing death and hospital readmission was inconsistent among recent meta-analyses.4,6 In addition, despite inclusion of patients with HF with preserved ejection fraction (HFpEF)7–11 and greater proportions of female and older patients in recent trials,12,13 the efficacy of CR in patients with HF who are elderly, female, frail, or have preserved ejection fraction remains unclear.
The association between CR participation and prognosis has been evaluated using real-world clinical data from registries and electronic databases.14–23 However, all observational CR studies to date involved patients with ischemic heart disease, and no large-scale studies have been conducted in patients with HF.
This study was planned and implemented to fill gaps between the real-world and randomized control trial-based CR evidence. The objective of this study was to estimate the impact of CR on prognosis in patients with HF. This study was also designed to clarify whether CR participation was associated with better prognosis in patients with HFpEF and frail patients with HF, subgroups in which little evidence based on interventional studies is available.24,25
Methods
The authors declare that all supporting data are available within the article and in the Data Supplement.
The multicenter retrospective cohort Agency for Medical Research and Development CR study was conducted at 15 Japanese hospitals in patients hospitalized for acute HF between January 1, 2007 and December 31, 2016. Consecutive patients admitted with HF were registered in the database by each participating hospital for some interval during this period. Patients who started CR after 180 days of discharge from index hospitalization were excluded to ensure we assessed the relevance of outpatient phase II CR. Patients who died during hospitalization, were censored within 14 days, were on maintenance dialysis, or were implanted with a left ventricular assist device were excluded. The study protocol was reviewed and approved by the institutional review boards of all participating institutions.
Data on demographics, diagnoses, comorbidities, prescribed medications, smoking status, New York Heart Association (NYHA) classification, blood pressure, heart rate, prior HF hospitalization, prior coronary revascularization, laboratory data (BNP [B-type natriuretic peptide], estimated glomerular filtration rate, albumin, and hemoglobin concentration, uric acid levels), need for assistance with activities of daily living (ADL) or instrumental ADL, and mobility limitation were recorded. Laboratory data were obtained on admission, prescribed medications, blood pressure, and heart rate were evaluated at discharge, and NYHA classification was evaluated on admission and discharge from hospital. Mobility limitation was defined as inability to walk without physical assistance at discharge.
Frailty Index
We calculated the cumulative deficit frailty score as a frailty index in accordance with previously established method26 using the 19 parameters listed in Table 1. Frailty index was calculated as the number of positive items divided by the total number of items. Zero indicates completely nonfrail and 1 indicates most frail. Categories of fit, mild frailty, moderate frailty, and severe frailty were defined by frailty index quartiles in our cohort.27
| Variable |
|---|
| History of hypertension |
| History of diabetes mellitus |
| History of coronary artery disease |
| History of cerebrovascular disease |
| History of atrial fibrillation |
| History of dyslipidemia |
| History of hyperuricemia (blood uric acid ≥7 mg/dL) |
| History of dementia |
| History of cancer |
| Prior myocardial infarction |
| Prior heart failure hospitalization |
| Anemia (Hgb: <13 g/dL for male, <12 g/dL for female) |
| Hypoalbuminemia (<3.5 g/dL) |
| Kidney dysfunction (eGFR<60 mL/min per 1.73 m2) |
| Obesity (>30 kg/m2) |
| Low body mass index (<20 kg/m2) |
| Older age (≥75 y) |
| Need for assistance with ADL or instrumental ADL |
| Mobility limitation |
| Frailty index=number of positive items/19 |
Cardiac Rehabilitation
CR use was defined as participation in at least one CR session within 3 months after discharge.16–19 Attendance was ascertained based on regional medical records.
Health insurance is mandatory in Japan, and CR has been covered for treatment of HF since 2007. Participating centers in this study generally performed CR according to the guidelines of the Japanese Circulation Society,28 which recommends that CR for patients with HF should begin with supervised CR, followed by a combination of supervised and nonsupervised CR 3 to 5 times a week for 5 months.
As patients can vary in baseline exercise capacity and personal training goals, the number of training hours is not stipulated in these exercise programs. As recommended in the Japanese CR guideline,28 the exercise therapy generally consisted of preparatory exercises such as stretching and moderate-intensity aerobic exercise. In addition, resistance training was added after stabilization. Subjects performed aerobic exercise at the anaerobic threshold, with heart rate calculated using the Karvonen formula (k=0.4–0.6), or intensity of 12 to 13 on the Borg scale. Patients with physical impairment or frailty performed functional training, such as balance training and physical therapy, to improve ADL performance.29,30 Multidisciplinary guidance about HF management was also provided to patients and their families.
Outcomes
The primary outcome was a composite of all-cause mortality and HF-related hospitalization. Secondary outcomes were all-cause mortality and HF hospitalization after discharge. Vital status and hospitalization data were collected from regional medical records.
Statistical Analysis
Propensity scores (PS) for individuals were determined by logistic regression analysis based on age; calendar year; sex; body mass index; left ventricular ejection fraction; NYHA classification on admission and discharge; systolic blood pressure; diastolic blood pressure; heart rate; HF cause (ischemic); prior hospitalization for HF; prior myocardial infarction; prior percutaneous coronary intervention; prior coronary artery bypass grafting; atrial fibrillation; diabetes mellitus; hypertension; cerebrovascular disease; dementia; cancer; orthopedic disease; prescription of ACE (angiotensin-converting enzyme) inhibitor/angiotensin II receptor blocker, β-blocker, aldosterone blocker, diuretics, and oral inotropes at discharge; living independently; current smoking status; mobility limitation; need for assistance with ADL or instrumental ADL; length of stay; estimated glomerular filtration rate; and hemoglobin, albumin, uric acid, log-BNP levels. The area under the receiver operating characteristic curve was calculated to evaluate the discrimination capability of this PS model.
Missing data were imputed using multiple imputation (additional information provided in Methods in the Data Supplement). Briefly, to account for missing values in multivariable modeling, we performed 20-fold multiple imputation using a Markov chain Monte Carlo technique31 to yield final regression coefficient estimates and P values.
The CR and non-CR groups were matched 1:1 for PS using calipers with width of 0.2 SD of PS.32 Covariate balance was assessed according to the standardized difference to determine the quality of PS matching; standardized mean differences for all covariates <0.1 was taken to indicate successful PS matching.33 Survival curves in the matched dataset were estimated by the Kaplan-Meier method and compared by the log-rank test. The hazard ratio (HR) and 95% CI were calculated using a Cox proportional hazard model. As a sensitivity analysis, Cox regression analyses (1) without adjustment, (2) adjusted for PS, and (3) adjusted for frailty index and all covariates used to generate PS were performed including all patients to assess the association between CR participation and the primary outcome.
Potential confounders related to the period between inclusion and the 3-month landmark to determine treatment status were also evaluated with landmark analysis used to account for immortal time bias (eg, onset of terminal disease preventing participating in CR).
Potential effect modification was assessed by subgroup analyses across age (stratified at 75 years), sex, HF cause (ischemic, nonischemic), BNP (stratified at median log-BNP), diabetes mellitus, hypertension, prior myocardial infarction, and ACE inhibitor/angiotensin II receptor blocker and β-blocker use. The P values for interactions between groups were calculated.
The association between CR participation and prognosis across frailty status was analyzed in all study patients. First, the validity of the frailty index in our patient cohort was assessed with Kaplan-Meier curves and multivariate Cox regression stratified by 4 categories of frailty index. We then assessed the relationship between CR participation and primary outcome for each frailty group using Kaplan-Meier curves and multivariate Cox regression. The adjustment variables in both of these Cox regressions were sex and major HF prognostic predictors including NYHA at discharge, log-BNP, prescription on ACE inhibitor or angiotensin II receptor blocker, and β-blocker that were not included in the frailty index.
The HFpEF and HFrEF subgroups stratified at left ventricular ejection fraction 50% were analyzed separately from the matched patients described above, as they are clinically different populations; they were PS-matched within each group using the methods described previously, and prognosis was compared using survival analysis in each group.
Statistical analyses were performed using SPSS 25.0 (IBM Corporation, New York, NY) and STATA version 16.0 (StataCorp, College Station, TX). Two-tailed P<0.05 was taken to indicate significance.
Results
A total of 4339 patients with HF were potentially eligible for inclusion, of which 1062 patients were excluded (Figure I in the Data Supplement). The study population consisted of 3277 patients with a mean age of 74.9±14.9 years, and 26% (862) participated in outpatient CR.
There were no differences in demographics, medications, or clinical characteristics after PS matching between CR participants and nonparticipants (n=796 pairs, a total of 1592 patients; Table 2). After PS matching, standardized mean differences were <0.1 for all covariates, a threshold commonly considered to indicate sufficient balance, including frailty-related parameters (ie, age, frailty index, dementia, and mobility status; Figure 1A). Figure 1B shows that the distributions of PS scores before and after PS matching were well balanced. The area under the receiver operating characteristic curve of this PS model was 0.78 (95% CI, 0.76–0.79).
| Before Propensity Score Matching | After Propensity Score Matching | ||||
|---|---|---|---|---|---|
| Non-CR Group, n=2415 | CR Group, n=862 | P Value | Non-CR Group, n=796 | CR Group, n=796 | |
| Age, y | 77.7 (18.2) | 66.9 (14.2) | <0.001 | 67.1 (16.3) | 67.8 (13.8) |
| Sex, male, n (%) | 1399 (58) | 531 (62) | 0.06 | 509 (64) | 486 (61) |
| Body mass index, kg/m2 | 23.3 (4.6) | 22.8 (4.4) | 0.013 | 23.0 (4.3) | 22.9 (4.4) |
| NYHA on admission, n (%) | 0.06 | ||||
| II | 309 (13) | 135 (16) | 112 (14) | 119 (15) | |
| III | 930 (39) | 306 (35) | 306 (38) | 286 (36) | |
| IV | 1126 (47) | 389 (45) | 347 (44) | 361 (45) | |
| NYHA at discharge, n (%) | 0.35 | ||||
| II | 1230 (51) | 534 (62) | 427 (54) | 483 (61) | |
| III | 548 (23) | 234 (27) | 246 (31) | 220 (28) | |
| IV | 20 (1) | 4 (0) | 5 (1) | 3 (0) | |
| LVEF, % | 45.5 (17.2) | 44.1 (17.0) | 0.032 | 44.7 (17.4) | 44.4 (16.9) |
| LVEF ≥50%, n (%) | 965 (40) | 338 (40) | 0.72 | 306 (38) | 314 (39) |
| SBP, mm Hg | 118 (23) | 120 (26) | 0.049 | 119 (27) | 118 (23) |
| DBP, mm Hg | 65 (14) | 70 (17) | <0.001 | 68 (16) | 68 (15) |
| Heart rate, bpm | 74 (16) | 79 (19) | <0.001 | 78 (19) | 77 (18) |
| Etiology, ischemic, n (%) | 328 (14) | 254 (29) | <0.001 | 210 (26) | 221 (28) |
| Prior HF hospitalization, n (%) | 868 (36) | 222 (26) | <0.001 | 213 (27) | 209 (26) |
| Prior myocardial infarction, n (%) | 506 (21) | 161 (19) | 0.17 | 147 (18) | 153 (19) |
| Current smoking, n (%) | 348 (15) | 141 (16) | 0.18 | 150 (19) | 132 (17) |
| Living alone, n (%) | 472 (20) | 165 (19) | 0.84 | 145 (18) | 149 (19) |
| Laboratory | |||||
| BNP, pg/mL | 661 (293–1316) | 514 (230–1052) | <0.001 | 536 (227–1026) | 521 (235–1063) |
| eGFR, mL/min per 1.73 m2 | 47.7 (25.8) | 52.9 (23.3) | <0.001 | 53.3 (23.4) | 52.8 (23.3) |
| Albumin, g/dL | 3.6 (0.5) | 3.7 (0.5) | <0.001 | 3.7 (0.5) | 3.7 (0.5) |
| Hemoglobin, g/dL | 11.9 (2.3) | 12.7 (2.4) | <0.001 | 12.7 (2.4) | 12.7 (2.4) |
| Comorbidity, n (%) | |||||
| Diabetes mellitus | 967 (40) | 346 (40) | 0.97 | 334 (42) | 325 (41) |
| Hypertension | 1691 (70) | 591 (69) | 0.44 | 537 (68) | 548 (69) |
| Atrial fibrillation | 959 (40) | 260 (30) | <0.001 | 264 (33) | 246 (31) |
| Prior stroke | 408 (17) | 121 (14) | 0.05 | 122 (15) | 113 (14) |
| Dementia | 226 (9) | 11 (1) | <0.001 | 11 (1) | 10 (1) |
| Cancer | 266 (11) | 70 (8) | 0.016 | 63 (8) | 68 (9) |
| Orthopedic | 336 (14) | 141 (16) | 0.08 | 117 (15) | 136 (17) |
| Treatment, n (%) | |||||
| HFrEF (LVEF<50%) | n=1450 | n=524 | n=490 | n=482 | |
| ACEI or ARB | 922 (64) | 432 (82) | <0.001 | 386 (79) | 395 (82) |
| β-Blocker | 1073 (74) | 437 (83) | <0.001 | 405 (83) | 402 (83) |
| Diuretics | 1161 (80) | 440 (84) | 0.05 | 400 (82) | 402 (83) |
| HFpEF (LVEF≥50%) | n=965 | n=338 | n=306 | n=314 | |
| ACEI or ARB | 592 (61) | 271 (80) | <0.001 | 236 (77) | 249 (79) |
| β-Blocker | 577 (60) | 233 (69) | 0.003 | 205 (67) | 211 (67) |
| Diuretics | 824 (85) | 257 (76) | <0.001 | 257 (84) | 236 (75) |
| ADL/frailty status | |||||
| Need for assistance with ADL or IADL, n (%) | 616 (26) | 139 (16) | <0.001 | 125 (16) | 128 (16) |
| Mobility limitation, n (%) | 603 (25) | 87 (10) | <0.001 | 80 (10) | 84 (11) |
| Frailty index | 0.33 (0.14) | 0.28 (0.13) | <0.001 | 0.28 (0.14) | 0.28 (0.13) |
Figure 1. Standardized mean difference and distribution of propensity scores before and after matching. A, Standardized mean difference before and after propensity matching. B, Distribution of propensity scores before and after matching. ACEI indicates angiotensin-converting enzyme inhibitor; ADL, activities of daily living; ARB, angiotensin II receptor blocker; BNP, B-type natriuretic peptide; CABG, coronary artery bypass grafting; CR, cardiac rehabilitation; eGFR, estimated glomerular filtration rate; HF, heart failure; LVEF, left ventricular ejection fraction; NYHA, New York Heart Association; and PCI, percutaneous coronary intervention.
The median (interquartile range) and mean follow-up were 2.4 years (1.3–4.3 years) and 2.7±1.6 years in the PS-matched cohort. During the follow-up period, there were 511 composite outcomes, including 223 (14%) all-cause mortalities and 392 (25%) HF hospitalizations.
Figure 2 shows the Kaplan-Meier survival curves for both groups after PS matching. The composite outcome rate was consistently and significantly lower in patients with CR during the entire period and within 3 months and after 3 months on landmark analysis. CR participation was associated with significant reductions in secondary outcomes, including all-cause mortality and HF hospitalization (Figure 3). Cox proportional hazard analysis indicated that CR participation was associated with lower rates of composite outcome, all-cause mortality, and HF hospitalization (HR, 0.77 [95% CI, 0.65–0.92]; P=0.003), and secondary outcomes, including all-cause mortality (HR, 0.67 [95% CI, 0.51–0.87]; P=0.003) and HF hospitalization (HR, 0.82 [95% CI, 0.67–0.99]; P=0.044). The associations between CR and outcomes were similar regardless of age, sex, cause, BNP, diabetes mellitus, hypertension, prior myocardial infarction, and prescribed medications (Figure 4).
Figure 2. Cardiac rehabilitation (CR) and composite of mortality and heart failure hospitalization. HR indicates hazard ratio.
Figure 3. Cardiac rehabilitation (CR) and all-cause mortality or heart failure hospitalization. HR indicates hazard ratio.
Figure 4. Cardiac rehabilitation (CR) and outcomes among subgroups. ACEI indicates angiotensin-converting enzyme inhibitor; ARB, angiotensin II receptor blocker; BB, β-blocker; BNP, B-type natriuretic peptide; and MI, myocardial infarction.
In the sensitivity analysis for primary outcome including all patients (n=3277, number of composite outcome=1262), CR participation was consistently associated with better outcome (unadjusted HR, 0.53 [95% CI, 0.46–0.61]; P<0.001], PS-adjusted HR, 0.81 [95% CI, 0.69–0.94]; P=0.006], and frailty index and all other covariates used to generate the PS-adjusted HR, 0.74 [95% CI, 0.64–0.86]; P<0.001]).
Figure II in the Data Supplement shows that the frailty index used in this study resulted in a normal distribution with a mean of 0.32±0.13. In the survival analysis, frailty index was strongly associated with the composite of mortality and HF hospitalization (Figure 5A). Kaplan-Meier survival curves stratified by frailty status and CR participation are shown in Figure 5B. Participation in CR was associated with a favorable outcome across all frailty categories, although the association was numerically weaker in the severe frailty group.
Figure 5. Frailty category and primary outcome, and differences in primary outcome by cardiac rehabilitation (CR) participation and frailty status. A, Association of frailty category with primary outcome. B, Differences in primary outcome by CR participation and frailty status. Categories of fit, mild frailty, moderate frailty, and severe frailty were defined by frailty index quartiles of our cohort. The cutoff values defining the frailty index quartiles were <0.21, 0.21–0.31, 0.32–0.41, and ≥0.42 for Fit to Severe Frailty, respectively. HR indicates hazard ratio.
Figure III in the Data Supplement shows that the distributions of PS scores after PS matching were well balanced both in the HFrEF and HFpEF groups. Participation in CR was associated with favorable outcomes in patients with HFrEF and HFpEF (HR, 0.69 [95% CI, 0.55–0.87]; P=0.002 in HFrEF; HR, 0.73 [95% CI, 0.55–0.98]; P=0.035 in HFpEF; Figure 6).
Figure 6. Cardiac rehabilitation (CR) and outcomes across left ventricular ejection fraction (LVEF) categories. HFpEF indicates heart failure with preserved ejection fraction; HFrEF, heart failure with reduced left ventricular ejection fraction; and HR, hazard ratio.
Discussion
In the present study, the association between CR participation and prognosis was evaluated retrospectively by following patients with HF at multiple centers. The major findings were as follows. All-cause mortality and risk of readmission because of HF were lower in CR participants even after PS matching according to factors related to HF prognosis. In addition, CR participation was also associated with a favorable outcome in patients with HFpEF and frail patients in which effectiveness had not been shown in randomized trials. These results suggest that CR improves the outcomes of patients with HF, especially in groups where treatments have not been established, such as patients with HFpEF and frail patients.
Previous Studies on CR for HF
Previous meta-analyses examined the effectiveness of CR in patients with HF.3–6 Long et al4 reported the results of a meta-analysis of 44 randomized controlled trials involving 5783 patients with HF. CR for patients with HF significantly reduced the risk of readmission because of HF by 41%, reduced risk of readmission because of all causes by 30%, and significantly improved QoL evaluated by the Minnesota Living With HF Questionnaire (average improvement 7.1 points [95% CI, 3.7–10.5] points). In addition, according to an individual patient data meta-analysis called ExTraMATCH II performed by collecting data from 3990 patients with HF in 13 intervention studies,3,6 CR improved 6-minute walk distance by a mean of 21 m (95% CI, 1.57–40.4 m) and Minnesota Living With HF Questionnaire score by 5.9 points (95% CI, 1.0–10.9 points) compared with controls. However, in these well-controlled studies, the mean age of the patients was 61.1 years, 73% of the patients were male, 70% were White, no data concerning Asians were included, 63% of the patients were NYHA class I–II, and 97% were patients with HFrEF.3 Moreover, these meta-analyses included many randomized controlled trials carried out before 2000, and few patients were on standard HF therapy.3
The present study has a number of strengths: (1) the cohort was older than in previous studies, (2) it had a reasonable percentage of females (38%) and patients with HFpEF (39%) after PS matching, (3) patients received contemporary standard treatment for HF, (4) there were similar percentages of patients with common comorbidities of HF relative to clinical cohorts (hypertension, diabetes mellitus, atrial fibrillation), and (5) strong prognostic factors for frailty were included, thereby excluding a potential healthy cohort bias. Despite its limitations as an observational study, this study provides an estimation of the effects of CR on HF prognosis in patients undergoing contemporary standard treatments with adjustment for prognostic factors, including frailty status.
Previous Observational Studies of Effects of CR on Prognosis
Many observational studies have evaluated effects of CR on prognosis in ischemic heart disease.14–23 These studies showed a 33% to 56% lower risk of death in patients participating in CR, consistent with our results indicating that risk of all-cause death was 33% lower in CR participants. There have been few large-scale studies of CR and prognosis of patients with HF due partly to noncoverage of CR as treatment for HF. In the United States, the US Centers for Medicare & Medicaid Services extended coverage for CR to patients with HF in 2014,34 but its target was limited to HF with EF≤35% and NYHA class II–IV symptoms despite being on optimal HF therapy for at least 6 weeks, and long-term effects on prognosis have not been evaluated. Moreover, in Europe, CR for HF is treated differently under health insurance between countries, and low prevalence has been reported.35
In Japan, CR for HF was covered by health insurance regardless of left ventricular ejection fraction in 2007.36 This insurance coverage has made estimation of effects on prognosis in patients with HF, including HFpEF, possible.
Mechanism of Association of CR With Favorable Prognosis
Exercise training improves autonomic balance, induces regression of atherosclerosis, improves exercise tolerance, alleviates depression, and improves skeletal muscle function, leading to improved outcomes.37–42 Drug adherence guidance, dietary and smoking cessation counseling, and psychological management are important components of CR,43,44 and such comprehensive multidisciplinary interventions may have played a role in the improvement in outcomes seen in this study.
No treatment has been demonstrated to improve HFpEF prognosis. HEpEF has many phenotypes, and as patients are often older, female, hypertensive, obese, frail, or sarcopenic, management of complications is an important component of treatment.24,25,45 As noted above, CR includes components absent in drug therapy, such as lifestyle management and interventions in sarcopenia/frailty. Indeed, when the results of previous intervention studies with drug therapy and exercise training for HFpEF were compared, no improvements in QoL or exercise tolerance were observed in any of the classic drug intervention studies.46–49 However, improvements in exercise tolerance and QoL have been consistently observed in exercise intervention studies for HFpEF.7–11 Exercise tolerance and QoL are important outcome indices that may affect prognosis of HF. Taken together, the results of previous studies and the present study suggest that multidisciplinary CR including exercise training is likely effective in patients with HFpEF.
Effects of CR in Frail Patients With HF
Our results suggested that CR may improve the prognosis of frail patients with HF. In a pilot study performed in patients with acute HF complicated by frailty, physical functioning was improved by tailor-made exercise training programs including a combination of gait training, balance training, resistance training, and aerobic exercise according to the patient’s condition.12 In a retrospective study, an improvement in exercise capacity was associated with favorable long-term outcomes in patients with advanced HF participating in multidisciplinary CR.50 These results suggest that improvement in physical function through CR may be an important goal in frail patients with HF.
Limitations
This study had several limitations: (1) it was a retrospective observational study; (2) selection bias of CR participants could not be excluded despite PS matching and adjusting; (3) sociodemographic, cardiopulmonary exercise testing, and longitudinal frailty data were unavailable; (4) details of the content and frequency of CR interventions in individual patients were not available; and (5) data about changes in treatment regimens after discharge, such as changes in prescription, medication adherence, and implantation of devices, were not available. We were unable to determine if higher frequency of CR visits leads to further improvement in prognosis, as demonstrated in observational studies in ischemic heart disease; this could not be tested in the present study.16,21 However, this study provides important insights for future clinical care of patients with HF because it is the first large-scale study on CR and prognosis of patients with HF and because subpopulations of patients for whom there is currently no effective treatment for HF (patients with HFpEF and frail patients) were included.
Conclusions
For patients with HF, CR participation was related to reduced risks of all-cause death and readmission because of HF. This relationship was observed in patients with HFpEF and frail patients with HF for whom no treatments to improve outcome have been established. This study provides a basis for further recognition of CR as standard treatment for patients with HF and important evidence for formulation of clinical guidelines and performance measures43 for hospitals necessary to adopt this therapy.
| ACE |
angiotensin-converting enzyme |
| ADL |
activities of daily living |
| BNP |
B-type natriuretic peptide |
| CR |
cardiac rehabilitation |
| HF |
heart failure |
| HFpEF |
heart failure with preserved ejection fraction |
| HFrEF |
heart failure with reduced ejection fraction |
| HR |
hazard ratio |
| NYHA |
New York Heart Association |
| PS |
propensity score |
| QOL |
quality of life |
Acknowledgments
The authors would like to thank Professor Massimo F. Piepoli for helpful comments and suggestions. The authors also thank all collaborating investigators for their contributions (Acknowledgment in the Data Supplement).
Sources of Funding
This study was supported by Research Grants from the Japan Agency for Medical Research and Development (AMED; 16ek0210058 h0001).
Footnotes
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