The Toronto Cardiac Rehabilitation and Secondary Prevention Program: 1968 Into the New Millennium
Bibliographic record
Abstract
Given our approach to the cardiac rehabilitation process, which is reflected in the program structure and services and our high patient volume, this program model is effective for us. The model permits us to treat relatively large number of patients with relatively small numbers of staff. On average, a patient attends 32 supervised exercise sessions at the Centre over the course of 12 months. This is actually fewer supervised sessions than the popular model of 3 times per week for 12 weeks. However, the 12-month program provides an additional 9 months to work with patients on heart-healthy lifestyle modifications. At the same time, we realize our model is not the model of choice for all people in all settings for a variety of reasons. We trust that some elements of our program may be of interest and beneficial to some readers. Undoubtedly, the program will continue to evolve and develop into the future. Currently, we are conducting a cardiac rehabilitation outcomes study in an effort to determine the appropriate duration of cardiac rehabilitation to achieve optimal physiological, psychological, and cost benefits for patients. This study involves more than 700 patients and the results are intended to help us further refine the program structure and selected program elements. As the new millennium approaches, healthcare system reforms and continuing changes in the delivery of medical care to cardiac patients present opportunities, challenges, and some uncertainties for cardiac rehabilitation. To continue our services to patients and the medical community, cardiac rehabilitation programs will need to identify and develop even more innovative and effective concepts in response to ever-changing local, regional, and national issues.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".