Low-Intensity Exercise Training Increases Heart Rate Variability in Patients With Peripheral Artery Disease
Bibliographic record
Abstract
Patients with peripheral artery disease (PAD), consistent with others with atherosclerotic occlusive disorders, have autonomic dysfunction (as measured by low heart rate variability [HRV]) that predisposes them to sympathetically mediated cardiac arrhythmias and sudden death. Exercise therapy has been shown to increase HRV in patients with coronary artery disease by increasing parasympathetic modulation of heart rate. This study quantified the circulatory and autonomic effects of a progressive, 12-week home-based, low-intensity (pain-free walking) exercise program in PAD and intermittent claudication. Participants ( N = 33, mean age 67.8 8.1 years) were randomly assigned to either a walking group ( n = 18), whose members performed a structured, 12-week, progressive walking program 5 days/week for 12 weeks, or a comparison group ( n = 15), whose members performed usual activities. Circulatory measures (heart rate, blood pressure, and rate pressure product) and autonomic measures (HRV) were obtained at the beginning (Week 1) and end (Week 12) of the study. Minimal change in circulatory measures occurred. However, spectral analysis of HRV revealed that autonomic function improved significantly in members of the walking group; specifically, there was an increase in parasympathetic and a decrease in sympathetic modulation. Members of the walking group also significantly increased maximal walking distance. These findings suggest that a structured, low-intensity, high-frequency walking program improves autonomic function by increasing HRV in patients with PAD.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".