Utilization of the Internet to Deliver Cardiac Rehabilitation at a Distance: A Pilot Study
Bibliographic record
Abstract
Less than 25% of eligible patients attend cardiac rehabilitation programs (CRP), with geographical proximity being a predominant barrier. Therefore, we undertook a pilot study to assess the feasibility and safety of using the Internet as a medium for delivery of an interactive "virtual" CRP (vCRP) to patients at a distance. Fifteen patients on the waiting list for a local hospital-based CRP were randomized to either an Internet-based vCRP or observational control. The vCRP consisted of on-line intake forms, one-on-one chat sessions with a nurse, dietitian, and exercise specialist, downloadable exercise heart rate monitoring, education and data monitoring of blood pressure, weight, and glucose. Participants were assessed for exercise capacity, risk factors, and lifestyle behaviors at baseline and at 12 weeks. Those in the vCRP logged onto the Internet-based CRP an average of 4.2 times per week. There were no adverse events in the vCRP participants. The vCRP group significantly improved their HDL-C, triglycerides, total cholesterol:HDL-C ratio, exercise capacity as assessed in metabolic equivalents, weekly physical activity, and exercise specific self-efficacy (p < 0.05). There were no significant improvements in the control group. Improvements in the vCRP group were similar to historical controls in a standard CRP. Feedback from exit interviews of the vCRP participants was unanimously positive. This Internet-based CRP resulted in clinically significant improvements in risk factors and exercise capacity similar to that of a standard CRP. The high user acceptance indicated that this program may have the potential to effectively manage patients who do not have access to traditional hospital-based CRP.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".