Cardiac Rehabilitation in Canada During COVID-19
Bibliographic record
Abstract
BACKGROUND: Cardiac rehabilitation programs (CRPs) had to change quickly in response to a shift in clinical priorities related to to the coronavirus disease 2019 (COVID-19). Yet, no study has examined the effect of COVID-19 on CRPs and if there has been an adequate transition to alternative programming. METHODS: To examine the status of CRPs during the COVID-19 pandemic, a web-based questionnaire was completed by CRP managers from April 23rd to May 14th, 2020. RESULTS: < 0.001. There was a significant reduction in patients with cognitive/communication/mobility deficits who were eligible to participate during the COVID-19 pandemic. Of respondents, 57%-82.6% reported safety concerns related to prescribing exercise to medically high-risk and vulnerable populations. CRPs transitioned from group-based to one-to-one delivery models->80% by phone and/or e-mail. Any tele-rehabilitation (one-to-one/group) was also used by 32.7% and 43.5% of CRPs to deliver exercise and education, respectively (mostly one-to-one). Resource barriers cited by open and closed CRPs were related to technology-no tele-rehabilitation, lack of equipment and patient access (35% of all barriers)-and 25.3% of barriers were owing to greater demands on staff time. CONCLUSIONS: Within 2-months of COVID-19 being declared a pandemic, 41.2% of CRPs were closed and almost half of employees redeployed. Less time-efficient one-to-one models of remote care, mostly by phone/e-mail, were adopted. Vulnerable populations were disproportionately affected, becoming ineligible owing to safety concerns. Strategies to open closed CRPs, admission of high-risk/vulnerable populations, and offering of group-based tele-rehabilitation should be a national priority.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".