Observing temporal trends in cardiac rehabilitation from 1996 to 2010 in Ontario: characteristics of referred patients, programme participation and mortality rates
Bibliographic record
Abstract
OBJECTIVES: We sought to describe temporal trends in the sociodemographic and clinical characteristics of participants referred to cardiac rehabilitation (CR), and its effect on programme participation and all-cause mortality over 14 years. SETTING: A large CR centre in Toronto, Canada. PARTICIPANTS: Consecutive patients between 1996 and 2010. PRIMARY AND SECONDARY OUTCOME MEASURES: Referrals received were deterministically linked to administrative data, to complement referral form abstraction. Out-of-hospital deaths were identified using vital statistics. Patients were tracked until 2012, and mortality was ascertained. Percentage attendance at prescribed sessions was also assessed. RESULTS: There were 29,171 referrals received, of which 28,767 (98.6%) were successfully linked, of whom 22,795 (79.2%) attended an intake assessment. The age of the referred population steadily increased, with more females, less affluent and more single patients referred over time (p<0.001). More patients were referred following percutaneous coronary intervention and less following coronary artery bypass graft surgery (p<0.001). The number of comorbidities decreased (p<0.001). Hypertension increased over time (p<0.001), yet the control of cholesterol steadily improved over time. The proportion of smokers decreased over time (p<0.001). Participation in CR significantly declined, and there were no significant changes in mortality. 3-year mortality rates were less than 5%. CONCLUSIONS: Characteristics of referred patients tended to reflect broader trends in risk factors and cardiovascular disease burden. Physicians appear to be referring more sociodemographically diverse patients to CR; however, programmes may need to better adapt to engage these patients to fully participate. More complex patients should be referred, using explicit criteria-based referral processes.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| 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".