Entering Cardiac Rehabilitation With Peripheral Artery Disease
Bibliographic record
Abstract
PURPOSE: Supervised exercise is recommended for patients with peripheral artery disease (PAD) and patients with coronary artery disease (CAD). Both conditions share common etiology as atherosclerotic diseases. The clinical profile, cardiorespiratory fitness, and exercise prescriptions of PAD, CAD, and patients with concomitant PAD and CAD (BOTH) have yet to be compared upon entry into cardiac rehabilitation (CR). METHODS: Cardiopulmonary, demographic, and anthropometric assessments were conducted at entry to CR between January 2006 and December 2017. RESULTS: Among 9701 consecutively enrolled patients, there were 94.6% with CAD (n = 9179), 1.5% with PAD (n = 143), and 3.9% with BOTH (n = 379). Only 5.4% (n = 522) of all patients entering CR had a diagnosis of PAD. Compared with CAD, patients with PAD and BOTH were older (mean ± SD = 62.5 ± 11.1 vs 67.9 ± 11.4 and 69.2 ± 9.8 yr, P < .01), had higher resting systolic blood pressure (124 ± 17 vs 130 ± 17 and 133 ± 18 mm Hg, P < .01), had lower cardiorespiratory fitness (19.7 ± 6.3 vs 15.6 ± 4.8 and 15 ± 4.5 mL/kg/min, P < .01), and were more likely to have diabetes (25% vs 35% and 41%, P < .01), abdominal obesity (39% vs 54% and 51%, P < .01), and initially prescribed lower-intensity exercise (84.4 ± 14.1 vs 74.1 ± 15.7 and 70.0 ± 14.6 m/min exercise pace, P < .01), reflecting the complex nature of patients diagnosed with PAD. CONCLUSIONS: Patients referred with PAD have a cardiovascular risk profile that places them at a greater risk for a repeat or first cardiac event compared with patients with CAD. Referral to structured exercise and risk factor modification programs should be considered to aid in the management of 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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".