Mortality Benefits of Cardiac Rehabilitation in Coronary Artery Disease Are Mediated by Comprehensive Risk Factor Modification: A Retrospective Cohort Study
Bibliographic record
Abstract
Background Cardiac rehabilitation (CR) is a multicomponent intervention to reduce adverse outcomes from coronary artery disease, but its mechanisms are not fully understood. The aims of this study were to examine the impact of CR on survival and cardiovascular risk factors, and to determine potential mediators between CR attendance and reduced mortality. Methods and Results A retrospective mediation analysis was conducted among 11 196 patients referred to a 12‐week CR program following an acute coronary syndrome event between 2009 and 2019. A panel of cardiovascular risk factors was assessed at a CR intake visit and repeated on CR completion. All‐cause and cardiovascular mortality were ascertained via health care administrative data sets at mean 4.2‐year follow‐up (SD, 2.81 years). CR completion was associated with reduced all‐cause (adjusted hazard ratio [HR], 0.67 [95% CI, 0.54–0.83]) and cardiovascular (adjusted HR, 0.57 [95% CI, 0.40–0.81]) mortality, as well as improved cardiorespiratory fitness, lipid profile, body composition, psychological distress, and smoking rates ( P <0.001). CR attendance had an indirect effect on all‐cause mortality via improved cardiorespiratory fitness ( ab =−0.006 [95% CI, −0.008 to −0.003]) and via low‐density lipoprotein cholesterol ( ab =−0.002 [95% CI, −0.003 to −0.0003]) and had an indirect effect on cardiovascular mortality via cardiorespiratory fitness ( ab =−0.007 [95% CI, −0.012 to −0.003]). Conclusions Cardiorespiratory fitness and lipid control partly explain the mortality benefits of CR and represent important secondary prevention targets.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".