Effectiveness of Home-Based Cardiac Rehabilitation and Its Importance During COVID-19
Bibliographic record
Abstract
Cardiac rehabilitation is a secondary prevention and disease-management opportunity for individuals living with cardiovascular disease. The COVID-19 pandemic has caused postponements and cancellations for many health services, including 41% of cardiac rehabilitation programs in Canada. Cardiac rehabilitation effectively reduces the risk of mortality, morbidity, and hospitalizations in cardiac clients. Without access, individuals face challenges to improve their health, which places them at risk of adverse outcomes. This paper argues that transitioning to home-based cardiac rehabilitation programs during the pandemic is a reasonable strategy to meet the ongoing rehabilitation needs of cardiac patients. Home-based cardiac rehabilitation programs utilize limited hospital or clinic visits because the majority of exercise is performed at home through regular communication with a case manager. Programs utilize a variety of resources, including technology, to regularly monitor, educate, and counsel clients. The programs’ flexibility and convenience overcome many multi-level barriers which normally impede participants from accessing services. These programs have proven to be equally effective, if not more effective than centre-based programs, at improving mortality, cardiac events, exercise capacity and modifiable risk factors. Home-based programs are a valid alternative to support and protect a vulnerable population, especially those at high risk if diagnosed with COVID-19. Transitioning to a home-based platform may be a challenge, but the Canadian Cardiovascular Society has provided practical approaches to support programs. Adapting current plans and developing new ones, utilizing appropriate resources, having a conservative exercise program, monitoring clients, emphasizing education, being flexible, and enhancing safety are key steps for a successful transition.
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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 | 0.007 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".