Sex differences in the neurophysiological and ventilatory responses to exercise : impact on the sensations of exertional dyspnea
Bibliographic record
Abstract
Purpose: This dissertation comprised three studies that examined the physiological, neurophysiological, and psychosocial mechanisms underlying sex differences in the multidimensional experience of exertional dyspnea. Methods: Study #1 (chapter 2) compared physiological, perceptual, and psychosocial factors between males and females who did versus did not select unsatisfied inspiration at peak exercise. Study #2 (chapter 3) investigated the effects of added ventilatory loading (dead space customized to 15 % of forced vital capacity) on sex differences in respiratory mechanics, neurophysiological responses, and the multidimensional components of exertional dyspnea. Study #3 (chapter 4) evaluated how relative dead space loading influenced respiratory muscle activation patterns and pressure generation in males and females. All studies used maximal incremental cycling exercise. Conclusions: We found that smaller absolute lung volumes were associated with higher intensity ratings of unsatisfied inspiration during exercise, and psychosocial factors, such as gender and anxiety, emerged as important contributors to sex differences in dyspnea perception (chapter 2). Although males and females exhibited distinct cardiorespiratory, respiratory mechanical, and neurophysiological responses, as well as respiratory muscle activation patterns with added dead space loading, these differences did not consistently translate to altered dyspnea perception during maximal cycling (chapters 3-4). Collectively, these findings suggest that despite well-established sex differences in respiratory anatomy and physiology, males and females appear to employ distinct reflexive respiratory muscle activation patterns that result in comparable perceptions of exertional dyspnea. Collectively, this work emphasizes that exertional dyspnea cannot be attributed to a single mechanism but instead reflects the complex interplay of anatomical, physiological, and psychosocial factors. Recognizing the reflexive respiratory muscle activation patterns in males and females may guide future research aimed at refining clinical assessment and developing more personalized approaches to managing dyspnea in aging populations and patient groups.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".