Importance of Completing Hybrid Cardiac Rehabilitation for Long-Term Outcomes: A Real-World Evaluation
Bibliographic record
Abstract
Community-based hybrid cardiac rehabilitation (CR) programs offer a viable alternative to conventional centre-based CR, however their long-term benefits are unknown. We conducted a secondary analysis of the CR Participation Study conducted in London, Ontario, between 2003 and 2006. CR eligible patients hospitalized for a major cardiac event, who resided within 60 min, were referred to a hybrid CR program; 381 of 544 (64%) referred patients initiated CR; an additional 1,498 CR eligible patients were not referred due to distance. For the present study, CR participants were matched using propensity scores to CR eligible non-participants who resided beyond 60 min, yielding 214 matched pairs. Subjects were followed for a mean (standard deviation, SD) of 8.56 (3.38) years for the outcomes of mortality or re-hospitalization for a major cardiac event. Hybrid CR participation was associated with a non-significant 16% lower event rate (Hazard Ratio [HR]: 0.84, 95% CI: 0.59⁻1.17). When restricting to pairs where CR participants achieved a greater than 0.5 metabolic equivalent exercise capacity increase (123 pairs), CR completion was associated with a 51% lower event rate (HR: 0.49, 95% CI: 0.29⁻0.81). Successful completion of a community-based hybrid CR program may be associated with decreased long-term mortality or recurrent cardiac events.
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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 | 0.009 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".