A Half-Century of Evidence-Based Cardiac Rehabilitation: A Historical Review
Bibliographic record
Abstract
OBJECTIVE: To review the achievements of cardiac exercise rehabilitation programs retrospectively and to identify continuing challenges to their success. METHODS: A review of files accumulated while working with the Toronto Rehabilitation Center, updated by articles identified by PUB-MED, OVID, and Google Scholar through February 2019. RESULTS: After the early lead of Israeli physicians, cardiac rehabilitation began in Ontario during the 1960s and quickly attracted a large case load. Recurrence rates of the patients recruited were low relative to those receiving standard medical treatment, even after allowing for differences in risk factors at entry to programs. Controlled trials began but were individually of insufficient in size to show a significant reduction in recurrences or mortality. Subsequently, multiple meta-analyses demonstrated a 20% to 25% reduction of all-cause and cardiac mortality over the first few years of follow-up in patients who persisted with their rehabilitation. Compliance continued a problem at many centers, but special features of the Toronto cardiac rehabilitation program sustained a compliance of 82.8% over 3 years. Although vigorous exercise increased the immediate risks of a recurrence 5- to 10-fold, this was more than offset by the long-term benefits of enhanced physical condition, and cardiac deaths were a rarity during either supervised or home-based exercise sessions. About a half of patients developed a depression immediately after infarction, but if encouraged to persist with prescribed exercise, their quality of life progressively improved. Among the wide variety of mechanisms underlying the benefits of exercise, gains of aerobic power seemed particularly important. With sustained training, the physical condition of some younger patients progressed to the point of participating successfully in marathon events. Older patients also benefited from sustained training, but for them, optimal results were likely associated with less rigorous physical demands. CONCLUSIONS: Research conducted in Toronto and elsewhere has established the benefits of exercise-centered cardiac rehabilitation. However, there remains a need to define the optimum timing of program onset, and the frequency, intensity, and duration of supervised training sessions. Return to blue-collar occupations also needs to be boosted, and the limited participation of eligible patients in available programs remains a continuing challenge.
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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 | 0.014 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.013 | 0.016 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.002 | 0.002 |
| 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".