Susceptibility to Muscle Fatigue and Lung Mechanics in Chronic Obstructive Pulmonary Disease
Bibliographic record
Abstract
Background: Contractile fatigue of the quadriceps occurs in a significant proportion of patients with COPD after constant-load cycling exercise. Dynamic hyperinflation, by altering cardiac output during exercise, could contribute to fatigue susceptibility in this population. The purpose of this study was to compare operational lung volumes during constant workrate exercise between COPD patients who do and those who do not develop contractile fatigue of the quadriceps (fatiguers vs non-fatiguers). Methods: Sixty-two patients with COPD (FEV1: 46±16%) completed a constant-load cycling test at 80% of the peak workrate achieved during progressive cycle ergometry. Ventilatory parameters were monitored breath-by-breath, while inspiratory capacity maneuvers were obtained every other minute during constant-load cycling. Quadriceps twitch force was measured with magnetic stimulation of the femoral nerve before and after the test. Muscle fatigue was defined as a post-exercise reduction in quadriceps twitch force of more than 15% of the resting value. Results: Forty patients (65%) developed muscle fatigue after constant-load cycling. No significant differences were found between fatiguers and non-fatiguers with respect to age, body mass index, resting lung function, peak oxygen consumption, and endurance time to constant-load exercise. Change in inspiratory capacity from rest to end-exercise (DIC) was similar between both subgroups (DIC: 0.56±0.32L vs 0.56±0.47L for fatiguers and non-fatiguers respectively, P=0.99). Conclusion: Susceptibility to muscle fatigue could not be predicted by exercise duration or by the degree of dynamic hyperinflation in 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".