Effect of obesity on respiratory mechanics during rest and exercise in COPD
Bibliographic record
Abstract
The presence of obesity in COPD appears not to be a disadvantage with respect to dyspnea and weight-supported cycle exercise performance. We hypothesized that one explanation for this might be that the volume-reducing effects of obesity convey mechanical and respiratory muscle function advantages. Twelve obese chronic obstructive pulmonary disease (COPD) (OB) [forced expiratory volume in 1 s (FEV(1)) = 60%predicted; body mass index (BMI) = 32 ± 1 kg/m(2); mean ± SD] and 12 age-matched, normal-weight COPD (NW) (FEV(1) = 59%predicted; BMI = 23 ± 2 kg/m(2)) subjects were compared at rest and during symptom-limited constant-work-rate exercise at 75% of their maximum. Measurements included pulmonary function tests, operating lung volumes, esophageal pressure, and gastric pressure. OB vs. NW had a reduced total lung capacity (109 vs. 124%predicted; P < 0.05) and resting end-expiratory lung volume (130 vs. 158%predicted; P < 0.05). At rest, there was no difference in respiratory muscle strength but OB had greater (P < 0.05) static recoil and intra-abdominal pressures than NW. Peak ventilation, oxygen consumption, and exercise endurance times were similar in OB and NW. Pulmonary resistance fell (P < 0.05) at the onset of exercise in OB but not in NW. Resting inspiratory capacity, dyspnea/ventilation plots, and the ratio of respiratory muscle effort to tidal volume displacement were similar, as was the dynamic performance of the respiratory muscles including the diaphragm. In conclusion, the lack of increase in dyspnea and exercise intolerance in OB vs. NW could not be attributed to improvement in respiratory muscle function. Potential contributory factors included alterations in the elastic properties of the lungs, raised intra-abdominal pressures, reduced lung hyperinflation, and preserved inspiratory capacity.
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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".