Cardiac rehabilitation: The emerging role of home-based approaches and telemedicine
Bibliographic record
Abstract
Outpatient cardiac rehabilitation programs provide supervised exercise training in addition to secondary prevention interventions. They are designed to speed recovery from acute cardiovascular events, benefit chronic patients and to improve quality of life. Alternative approaches to the delivery of supervised cardiac rehabilitation include home-based programs, disease management and lifestyle health coaching interventions, and other internet-based case management systems. The effectiveness of home-based programs was evaluated in several randomized trials. There was no evidence of a difference in mortality, reinfarction, revascularization, cardiac-associated hospitalization, or exercise capacity between the two modes of intervention. Other alternatives include community-based group programs and the use of telemedicine. Use of mobile health technologies may further expand cardiac rehabilitation availability. Telehealth exercise cardiac rehabilitation appears to be at least as effective as center-based cardiac rehabilitation in improving modifiable cardiovascular risk factors and functional capacity. It identifies the option of telehealth and the technologic advances to provide more comprehensive, responsive, and interactive interventions for individuals for whom center-based rehabilitation is not feasible. The attractiveness of telemedicine models is the potential to improve participation of patients in structured with its short term and long-term benefits.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".