Abstract 19130: Referral to Cardiac Rehabilitation: A Quality Indicator Associated with Reduced Mortality
Bibliographic record
Abstract
Background: Cardiac Rehabilitation (CR) is an efficacious, evidence based treatment for reducing mortality and hospitalization in subjects with coronary artery disease (CAD). CR referral is an indicator of quality care in CAD patients. However, not all eligible subjects are referred for CR. The objective of this study was to assess predictors of referral to CR and the association between referral and mortality. Methods: All subjects who underwent coronary angiography between 1995 and 2009 and were found to have CAD were included in this study (n=25,958, 24.6% female). Referral to CR and subsequent attendance were evaluated. Baseline characteristics were compared between those who were referred and not. Logistic regression models predicting referral were developed. Using cox proportional hazards models, survival was then compared across those who were not referred (NR), referred and did not attend, and referred and did attend. Results: Of those subjects with CAD, 10236 (39.4%) were referred to CR; 58.4% of those referred attended CR. Rates of referral increased from 20.7 to 65.3% over the course of the study (p<0.0001). In multivariate models, older age, being female, and diabetes all predicted non-referral (all p<0.0001). Relative to the NR, those who were referred and did not attend had a hazard ratio (HR) for mortality of 0.55 (95% CI 0.51, 0.60); those who were referred and attended had a HR of 0.26 (95% CI 0.24, 0.29). When adjusted for age, sex, CAD severity, treatment (surgical, interventional, medical) and all clinical covariates, subjects who were referred and did not attend had a HR of 0.76 (95% CI 0.70, 0.82) and subjects who were referred and attended had a HR of 0.42 (95% CI 0.38, 0.46) for death relative to those who were NR. Conclusion: While CR referral rates have improved over time, they remain suboptimal. High-risk subjects are the most likely to remain un-referred. Given the association between CR referral and reduced mortality, referral to CR is a justifiable quality indicator for CAD patient care. Efforts to improve referral should be undertaken.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 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) | 0.005 | 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".