The Integrative Physiology of Exercise Training in Patients with COPD
Bibliographic record
Abstract
Supervised exercise training (EXT) as part of pulmonary rehabilitation is arguably the most effective intervention for improving exercise tolerance in patients with chronic obstructive pulmonary disease (COPD). In the current review, we focus on the physiological rationale for EXT and the expected physiological benefits that can be achieved in patients who can be exposed to sufficiently high training stimuli. Thus, after a brief consideration of the mechanisms of exercise limitation and their sensory consequences, we expose the potential beneficial effects of EXT on respiratory mechanical and peripheral muscular adaptations to exercise. The available evidence indicates that changes in exertional ventilation, breathing pattern, operating lung volumes and static respiratory muscle strength after EXT are modest and often inconsistent. Inspiratory muscle training may have a role in patients showing inspiratory weakness pre-rehabilitation. Beneficial changes in peripheral muscles can be seen in those who can tolerate higher training intensity, particularly using combined resistance and dynamic (including interval) exercise. It should be recognised, however, that it might not be feasible to reach meaningful physiological training effects in many frail elderly patients with advanced respiratory mechanical and pulmonary gas exchange derangements with serious co-morbidities (such as cardiac and peripheral vascular disease). These potential shortcomings should not discourage the use of pulmonary rehabilitation as an effective strategy to improve patients' capacity to tolerate physical activity. Currently, the greatest challenge is to develop effective strategies to ensure that these important gains in functional capacity are translated into sustained increases in daily physical activity for patients with COPD.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".