Differences in respiratory muscle activity during cycling and walking do not influence dyspnea perception in obese patients with COPD
Bibliographic record
Abstract
In patients with combined obesity and chronic obstructive pulmonary disease (COPD), dyspnea intensity at matched work rates during weight-supported cycling and weight-bearing walking is similar, despite consistent metabolic differences between test modalities. The present study examined the influence of differences in activity of the diaphragm and abdominal muscles during cycling and walking on intensity and quality of dyspnea at matched ventilation in obese patients with COPD. We compared respiratory muscle activity patterns and dyspnea ratings during incremental cycle and treadmill exercise tests, where work rate was matched, in 12 obese (body mass index 36.6 ± 5.4 kg/m(2); mean ± SD) patients with moderate COPD. We used a multipair electrode-balloon catheter to compare electromyography of the diaphragm and esophageal, gastric, and transdiaphragmatic pressures during the two exercise tests. Ventilation, breathing pattern, operating lung volumes, global respiratory effort, and electrical activation of the diaphragm were similar across exercise modalities for a given work rate. The cycling position was associated with greater neuromuscular efficiency of the diaphragm (P < 0.01), greater diaphragm use (P < 0.01) measured by the ventilatory muscle recruitment index, and less expiratory muscle activity compared (P < 0.01) with treadmill walking. However, intensity and quality of dyspnea were similar between exercise modalities. In obese patients with COPD, altered respiratory muscle activity due to body position differences between cycling and walking did not modulate perceived dyspnea when indirect measures of respiratory neural drive were unchanged.
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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 | 0.000 |
| 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) | 0.001 | 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".