Outcomes of a Remote Cardiac Rehabilitation Program for Patients Undergoing Atrial Fibrillation Ablation: Pilot Study
Bibliographic record
Abstract
BACKGROUND: Risk factor modification, in particular exercise and weight loss, has been shown to improve outcomes for patients with atrial fibrillation (AF). However, access to structured supporting programs is limited. Barriers include the distance from appropriate facilities, insurance coverage, work or home responsibilities, and transportation. Digital health technology offers an opportunity to address this gap and offer scalable interventions for risk factor modification. OBJECTIVE: This study aims to assess the feasibility and effectiveness of a 12-week asynchronous remotely supervised exercise and patient education program, modeled on cardiac rehabilitation programs, in patients with AF. METHODS: A total of 12 patients undergoing catheter ablation of AF were enrolled in this pilot study. Participants met with an exercise physiologist for a supervised exercise session to generate a personalized exercise plan to be implemented over the subsequent 12-week program. Disease-specific education was also provided as well as instruction in areas such as blood pressure and weight measurement. A digital health toolkit for self-tracking was provided to facilitate monitoring of exercise time, blood pressure, weight, and cardiac rhythm. The exercise physiologist remotely monitored participants and completed weekly check-ins to titrate exercise targets and provide further education. The primary end point was program completion. Secondary end points included change in self-tracking adherence, weight, 6-minute walk test (6MWT), waist circumference, AF symptom score, and program satisfaction. RESULTS: and CHADs2VASC (Congestive Heart Failure, Hypertension, Age [≥75 years], Diabetes, Stroke/Transient Ischemic Attack, Vascular Disease, Age [65-74 years], Sex [Female]) of 1.5. A total of 11/12 (92%) participants completed the program, with 94% of expected check-ins completed and 2.9 exercise sessions per week. Adherence to electrocardiogram and blood pressure tracking was fair at 81% and 47%, respectively. Significant reductions in weight, waist circumference, and BMI were observed with improvements in 6MWT and AF symptom scores (P<.05) at the completion of the program. For program management, a mean of 2 hours per week or 0.5 hours per patient per week was required, inclusive of time for follow-up and intake visits. Participants rated the program highly (>8 on a 10-point Likert scale) in terms of the impact on health and wellness, educational value, and sustainability of the personal exercise program. CONCLUSIONS: An asynchronous remotely supervised exercise program augmented with AF-specific educational components for patients with AF was feasible and well received in this pilot study. While improvements in patient metrics like BMI and 6MWT are encouraging, they should be viewed as hypothesis generating. Based on insights gained, future program iterations will include particular attention to improved technology for data aggregation, adjustment of self-monitoring targets based on observed adherence, and protocol-driven exercise titration. The study design will need to incorporate strategies to facilitate the recruitment of a diverse and representative participant cohort.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".