Lean body mass and the cardiovascular system constitute a female-specific relationship
Bibliographic record
Abstract
Recent evidence points toward a link between lean body mass (LBM) and cardiovascular capacity in women. This study aimed at determining the sex-specific relationship of LBM with central and peripheral circulatory variables in healthy women and men ( n =70) matched by age (60±12 years versus 58±15 years), physical activity, and cardiovascular risk factors. Regional (legs, arms, and trunk) and whole-body (total) body composition were assessed via dual-energy x-ray absorptiometry. Cardiac structure, function, and central/peripheral hemodynamics were measured via transthoracic echocardiography and the volume-clamp method at rest and peak incremental exercise. Regression analyses determined sex-specific relationships between LBM and cardiovascular variables. Regional and total LBM were lower in women than men ( P <0.001), with little overlap between sexes. Leg and arm LBM positively associated with left ventricular (LV) internal resting dimensions in women ( r ≥0.53, P ≤0.002) but not men ( P ≥0.156). Leg, arm, and total LBM only associated with LV relaxation in women ( r ≥0.43, P ≤0.013). All LBM variables strongly associated with LV volumes at peak exercise in women ( r ≥0.54, P ≤0.001) but not men and negatively associated with total peripheral resistance at peak exercise in women ( r ≥0.43, P ≤0.023). Adjustment by adiposity-related or cardiovascular risk factors did not alter results. In conclusion, leg and arm LBM independently associate with internal cardiac dimensions, ventricular relaxation, and systemic vascular resistance in a sex-specific manner, with these relationships exclusively present in women.
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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) | 0.003 | 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".