Do isolated leg exercises improve dyspnea during exercise in chronic obstructive pulmonary disease?
Bibliographic record
Abstract
Dyspnea, the subjective feeling of shortness of breath, is a hallmark feature of chronic obstructive pulmonary disease (COPD). Pulmonary rehabilitation (PR) programs aim to improve dyspnea, thereby increasing exercise tolerance and health-related quality of life in patients with COPD. Exercise training is proven to be an essential component of PR; however, there is no consensus regarding which training modality confers the greatest therapeutic benefit. Secondary to pulmonary impairment, many COPD patients develop limb muscle dysfunction (LMD), particularly in the leg muscles. Mounting evidence suggests that peripheral limitation to exercise as a result of LMD is frequent in patients with COPD. LMD of the legs, or lower limb muscle dysfunction, has been shown to markedly influence ventilatory and dyspnea responses to exercise. Accordingly, isolated training of leg muscles may contribute to reducing dyspnea and increase exercise tolerance in patients with COPD. Indeed, relative to the largely irreversible impairment of the pulmonary system, the leg muscles are an important site by which to improve patients' level of function and quality of life. Isolated leg exercises have been shown to improve LMD and may constitute an effective training modality to improve dyspnea and exercise tolerance in COPD within the context of PR.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".