Sex differences in pulmonary and systemic vascular function at rest and during exercise in healthy middle-aged adults
Bibliographic record
Abstract
Abstract Our aim was to conduct a sex-disaggregated analysis of pulmonary and systemic vascular function in healthy individuals both at rest and during submaximal exercise. Healthy individuals underwent right-heart catheterization at rest and during submaximal cycling. Hemodynamic data were collected in a control state and with moderate exercise. Pulmonary and systemic vascular variables including: compliance, resistance, and elastance were calculated, indexed to body surface area (BSA), adjusted for age and compared between male and female sex. Thirty-six individuals (18M/18F; 54±7 vs. 58±6 years, p=0.04) were included. When adjusted for age and indexed to BSA, total pulmonary resistance (TPulmR) (516±73 vs. 424±118 WU•m-2, p=0.03) and pulmonary arterial elastance (PEa) (0.41±0.1 vs. 0.32±0.1 mmHg•mL-1•m2, p=0.03) were higher in females vs. males. Both pulmonary (Cpa) and systemic compliance (Csa) were lower in females vs. males however lost significance with adjustment for age. Systemic arterial elastance (SEa) was higher in females (1.65±0.29 vs. 1.31±0.24 mmHg•mL-1, p=0.05). Secondary analyses demonstrated significant correlations between age and PVR (r=0.33, p=0.05), TPulmR (r=0.35, p=0.04), Cpa (r=-0.48, p<0.01), and PEa (r=0.37, p=0.03). During exercise, there were greater increases in TPulmR (p=0.02) and PEa (p=0.01) in females vs. males. TPulmR and PEa are significantly higher at rest and exercise in females vs. males. Cpa and Csa were lower in females, however this may have been confounded by age. Our results are consistent with the notion that indices of pulmonary and systemic vascular load are increased related to both older age and female sex.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".