Exercise Training and Peripheral Arterial Disease
Bibliographic record
Abstract
Peripheral arterial disease (PAD) is a common vascular disease that reduces blood flow capacity to the legs of patients. PAD leads to exercise intolerance that can progress in severity to greatly limit mobility, and in advanced cases leads to frank ischemia with pain at rest. It is estimated that 12 to 15 million people in the United States are diagnosed with PAD, with a much larger population that is undiagnosed. The presence of PAD predicts a 50% to 1500% increase in morbidity and mortality, depending on severity. Treatment of patients with PAD is limited to modification of cardiovascular disease risk factors, pharmacological intervention, surgery, and exercise therapy. Extended exercise programs that involve walking approximately five times per week, at a significant intensity that requires frequent rest periods, are most significant. Preclinical studies and virtually all clinical trials demonstrate the benefits of exercise therapy, including improved walking tolerance, modified inflammatory/hemostatic markers, enhanced vasoresponsiveness, adaptations within the limb (angiogenesis, arteriogenesis, and mitochondrial synthesis) that enhance oxygen delivery and metabolic responses, potentially delayed progression of the disease, enhanced quality of life indices, and extended longevity. A synthesis is provided as to how these adaptations can develop in the context of our current state of knowledge and events known to be orchestrated by exercise. The benefits are so compelling that exercise prescription should be an essential option presented to patients with PAD in the absence of contraindications. Obviously, selecting for a lifestyle pattern that includes enhanced physical activity prior to the advance of PAD limitations is the most desirable and beneficial.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".