Respiratory Consequences of Mild-to-Moderate Obesity: Impact on Exercise Performance in Health and in Chronic Obstructive Pulmonary Disease
Bibliographic record
Abstract
In many parts of the world, the prevalence of obesity is increasing at an alarming rate. The association between obesity, multiple comorbidities, and increased mortality is now firmly established in many epidemiological studies. However, the link between obesity and exercise intolerance is less well studied and is the focus of this paper. Although exercise limitation is likely to be multifactorial in obesity, it is widely believed that the respiratory mechanical constraints and the attendant dyspnea are important contributors. In this paper, we examined the evidence that critical ventilatory constraint is a proximate source of exercise limitation in individuals with mild-to-moderate obesity. We first reviewed existing information on exercise performance, including ventilatory and perceptual response patterns, in obese individuals who are otherwise healthy. We then considered the impact of obesity in patients with preexisting respiratory mechanical abnormalities due to chronic obstructive pulmonary disease (COPD), with particular reference to the effect on dyspnea and exercise performance. Our main conclusion, based on the existing and rather sparse literature on the subject, is that abnormalities of dynamic respiratory mechanics are not likely to be the dominant source of dyspnea and exercise intolerance in otherwise healthy individuals or in patients with COPD with mild-to-moderate obesity.
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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 | 0.001 |
| 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 | 0.001 | 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".