Rural cardiac rehabilitation: a 20-year success story.
Bibliographic record
Abstract
INTRODUCTION: Data are lacking on long-term participation in a clinically supervised cardiac rehabilitation program in a rural setting. We sought to determine whether there were sustained improvements in physiologic measures and discover what restorative and deteriorative processes took place over time. METHODS: We retrospectively analyzed the records of patients who were enrolled for a least 1 year in the Healthy Hearts Cardiac Rehabilitation Program. Data from stress tests were tracked for up to 18 years to determine whether there were any sustained improvements and what factors were associated with restorative and deteriorative processes. RESULTS: We analyzed data from 85 participants. The mean age of the participants was 72 years, and the mean length of participation was 8 years. Duration of stress testing significantly (p < 0.01) increased by a mean of 15% from the first year to the second year, with a corresponding increase in estimated metabolic equivalent of task (MET) level (Cohen d = 0.82). The increase in duration was sustained into the ninth year, with an overall increase of 35% compared with the first year of testing. After the ninth year, the duration and estimated MET levels declined. CONCLUSION: Participants in the cardiac rehabilitation program demonstrated improved duration of stress testing, and stable rate-pressure product, blood pressure and resting heart rate during long-term participation in the program.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".