Improving Access to Cardiac Rehabilitation Using the Internet: A Randomized Trial
Bibliographic record
Abstract
Cardiac rehabilitation (CR) is essential for secondary prevention, yet only 10%-30% of eligible patients attend as geographical proximity is a major barrier. We evaluated a 'virtual' CR program (vCRP) delivered by the Internet to patients in small urban and rural areas. In our study, in-patients (n=78) with acute coronary syndrome or post-revascularization were randomized to usual care (UC) or vCRP. The vCRP was a four-month program that included heart rate monitoring; physiologic data capture; education sessions; ask-an-expert sessions; and chat sessions with a nurse, exercise specialist and dietitian. Participants were assessed at baseline and four months, and followed for another 12 months. The primary outcome was change in maximal time on the treadmill stress test (MTT) between groups adjusted for age, sex, diabetes status and Internet use for health information. The vCRP resulted in a greater increase in MTT by 45.7 seconds (95% CI: 1.0, 90.5) compared to usual care (p=0.045). Cholesterol levels and dietary quality improved in the vCRP compared to the UC group. Participants perceived the vCRP to be an accessible, convenient and effective way to received healthcare. Eleven (30%) and 6 (18%) participants in the UC and vCRP groups, respectively, had cardiovascular-related events (p=0.275). In conclusion, the vCRP was safe and effective and resulted in sustainable risk reduction without the requirement of face-to-face visits and directly monitored exercise.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".