Exercise-based cardiac rehabilitation for coronary heart disease: the CaReMATCH individual participant data meta-analysis
Bibliographic record
Abstract
AIMS: The effectiveness of exercise-based cardiac rehabilitation (ExCR) for coronary heart disease (CHD) has been debated during the past decade. The objectives of the Cardiac Rehabilitation Meta-Analysis of Trials in people with CHD using individual participant data (IPD) (CaReMATCH) study were to (i) provide contemporary estimates on the effectiveness of ExCR for CHD and (ii) examine potential differential effects of ExCR across subgroups. METHODS AND RESULTS: Individual participant data from randomized controlled trials comparing ExCR with no ExCR controls were pooled. To reflect contemporary ExCR practice, trials had to be published since 2010. The outcomes of all-cause and cardiovascular disease (CVD)-related mortality and hospitalization and health-related quality of life (HRQoL) were analysed. From 30 eligible trials (10 677 participants), IPD were obtained from eight trials (4975 participants, 93.5% post-myocardial infarction). Compared with controls, participation in ExCR resulted in a lower risk for all-cause [hazard ratio (HR) 0.68, 95% confidence interval (CI): 0.53, 0.87] and CVD-related hospitalization (HR 0.62, 95% CI: 0.47, 0.83) and higher HRQoL up to 12 months of follow-up (mean difference in utility index: 0.032, 95% CI: 0.003, 0.061). No differences were found in all-cause and CVD mortality (HR 0.99, 95% CI: 0.74, 1.32; HR 0.80, 95% CI: 0.32, 2.04, respectively). Subgroup analyses showed stronger improvements of HRQoL with ExCR in people with lower HRQoL and lower education level and larger reductions in hospitalization risk in those with a lower left ventricular ejection fraction, lower baseline exercise capacity, beta-blockers use, and with a previous history of CVD. No other subgroup effects were observed. CONCLUSION: Our IPD meta-analysis, reflecting trials published since 2010, highlighted that contemporary ExCR is effective in reducing risk of hospitalization and improving HRQoL in those with CHD. Importantly, we reveal treatment benefits to be robust and consistent across most participant subgroups. Together, these data support the class I recommendation of international clinical guidelines that ExCR should be offered to all people with CHD. REGISTRATION: PROSPERO: CRD42020204988.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.022 | 0.044 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.045 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".