Combined Effects of Obesity and Chronic Obstructive Pulmonary Disease on Dyspnea and Exercise Tolerance
Bibliographic record
Abstract
RATIONALE: Severity of lung hyperinflation is known to influence the extent of dyspnea and exercise intolerance among patients with chronic obstructive pulmonary disease (COPD) with similar degrees of airway obstruction. Lung volume components are consistently affected by body mass index (BMI) in health and in disease. OBJECTIVES: To explore the complex interactions between obesity, lung hyperinflation, dyspnea, and exercise performance in COPD. METHODS: We compared dyspnea intensity ratings and ventilatory responses (breathing pattern, operating lung volumes, and gas exchange) during symptom-limited incremental cycle exercise in well-characterized groups of 18 obese (mean BMI +/- SD, 35 +/- 4 kg/m(2)) and 18 normal-weight (mean BMI +/- SD, 22 +/- 2 kg/m(2)) patients with moderate to severe COPD. MEASUREMENTS AND MAIN RESULTS: Groups were well matched for FEV(1) (mean 49% predicted) and diffusing capacity (means >70% predicted), but resting lung hyperinflation (end-expiratory lung volume [EELV]) was significantly reduced in association with increasing BMI (P < 0.005). In the obese patients, peak symptom-limited oxygen uptake was increased (P < 0.01) and dyspnea ratings at a standardized ventilation were decreased (P < 0.01) compared with normal-weight patients. Ratings of dyspnea intensity at a standardized ventilation during exercise correlated well with the concurrent dynamic EELV/total lung capacity (TLC) ratio (r = 0.68; P < 0.00001) and with the resting EELV/TLC (r = 0.67; P < 0.00001). CONCLUSIONS: The combined mechanical effects of obesity and COPD reduced operating lung volumes at rest and throughout exercise with favorable influences on dyspnea perception and peak oxygen uptake during cycle ergometry.
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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) | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 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".