Cardiac Rehabilitation Component Attendance and Impact of Intervening Clinical Events, as Well as Disease Severity and Risk Factor Burden
Bibliographic record
Abstract
PURPOSE: To examine: (1) the rate of clinical events precluding cardiac rehabilitation (CR) continuation, (2) CR attendance by component in those without events, and (3) the association between disease severity (eg, tobacco use, diabetes, and depression) and component attendance (eg, exercise, diet, stress management, and tobacco cessation). METHODS: Retrospective analysis of electronic records of the CR program in London, Ontario, from 1999 to 2017. Patients in the supervised program are offered exercise sessions 2 times/wk with a minimum of 48 prescribed sessions tailored to patient need. Patients attending ≥1 session without major factors that would limit their exercise ability were included. Intervening events were recorded, as was component attendance. RESULTS: Of 5508 enrolled, supervised patients, 3696 did not have a condition that could preclude exercise. Of those enrolled, one-sixth (n = 912) had an intervening event; these patients were less likely to work, more likely to have medical risk factors, had more severe angina and depression, and lower functional capacity. The remaining cohort attended a mean of 26.5 ± 21.3 sessions overall (median = 27; 19% attending ≥48 sessions), including 20.5 ± 17.4 exercise sessions (median = 21). After exercise, the most common components attended were individual dietary and psychological counseling. Patients with more severe angina and depressive symptoms as well as tobacco users attended significantly fewer total sessions, but more of some specific components. CONCLUSIONS: In one-sixth of patients, CR attendance and completion are impacted by clinical factors beyond their control. Many patients are taking advantage of components specific to their risk factors, buttressing the value of individually tailored, menu-based programming.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".