Physiological mechanisms of increased activity-related dyspnea in obesity
Bibliographic record
Abstract
Obesity is an independent risk factor for troublesome activity-related dyspnea. The mechanisms of increased exertional dyspnea in obesity remain poorly understood and represented the primary focus of our study. To this end, ventilation (VE), breathing pattern, dynamic operating lung volume, diaphragm EMG activity expressed as a percentage of maximum (EMGdi%max; an index measure of neural respiratory drive) and dyspnea responses to symptom-limited incremental cycle exercise testing were compared between 30 obese (OB; 15M:15W; mean±SE BMI=33.6±0.8 kg/m2; 43±1% fat mass; 137±3% ideal body mass) and 30 non-obese (NOB; 15M:15W; BMI=21.8±0.3 kg/m2; 28±1% fat mass; 89±1% ideal body mass) adults aged 18-40 yrs. After adjusting for differences in lean body mass (OB, 56±2 vs. NOB, 46±2 kg), VE, breathing frequency, EMGdi%max and dyspnea were higher at any standardized submaximal work rate during exercise in OB vs. NOB. Mean values of inspiratory capacity (IC) and inspiratory reserve volume (IRV) were higher (by ∼260 mL and ∼400 mL, respectively) at rest and at any VE during exercise in OB vs. NOB. Interestingly, EMGdi%max-IRV and dyspnea-IRV relationships were parallel shifted to the left during exercise in OB vs. NOB. By contrast, EMGdi%max-VE, dyspnea-VEand dyspnea-EMGdi%max relationships were similar throughout much of exercise in OB vs. NOB. In conclusion, mechanical adaptations of the respiratory system, including recruitment of resting (pre-exercise) IC and IRV, helped to preserve EMGdi%max-VE relationships during exercise in OB vs. NOB. Under these circumstances, the increased perception of exertional dyspnea in OB likely reflected the awareness of increased neural respiratory drive.
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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 | 0.000 |
| 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 | 0.000 | 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".