Effect of obesity on constant workrate exercise in hyperinflated men with COPD
Bibliographic record
Abstract
BACKGROUND: Chronic obstructive pulmonary disease (COPD) and a high body mass index (BMI) can both affect pulmonary volumes as well as exercise tolerance, but their combined effect on these outcomes is not well known. The aim of this study was to investigate the effects of increased BMI during constant workrate cycle ergometry in patients with COPD. METHODS: Men with COPD and hyperinflation were divided according to World Health Organization BMI classification: 84 normal BMI (NBMI), 130 overweight (OW) and 64 obese (OB). Patients underwent spirometric and lung volumes assessment and an incremental cycling exercise test. This was followed by a constant workrate exercise test (CET) at 75% of peak capacity. Inspiratory capacity and Borg dyspnea scores were measured at baseline, during and at the end of CET. RESULTS AND DISCUSSION: FEV1 % predicted was not different across BMI classes. Total lung capacity and functional residual capacity were significantly lower in OB and OW compared to NBMI patients. Peak VO2 in L x min(-1) was significantly higher in OB and OW patients than in NBMI patients. CET time was not different across BMI classes (p = 0.11). Changes in lung volumes and dyspnea during CET were not different between BMI categories. CONCLUSIONS: OB and OW patients with COPD had a higher peak VO2 than their lean counterparts. Endurance time, dyspnea and changes in lung volumes during CET were similar between BMI categories.
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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 | 0.002 |
| 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".