Age- and Sex-Differences in Cardiac Characteristics Determined by Echocardiography in Masters Athletes
Bibliographic record
Abstract
Background Cardiac function and morphology are known to differ between men and women. Sex differences seen with echocardiography have not been studied systematically in masters athletes. Purpose To evaluate sex differences in cardiac structure, function and left ventricular (LV) systolic global longitudinal strain among masters athletes. Methods This cross-sectional study comprises of 163 masters athletes (M= 109, 60 ± 12 years;F= 55, 57 ± 12 years, range 36–91 years) who participated at the 23rd World Masters Athletics Championship held in Málaga, Spain. All athletes underwent state-of-the-art echocardiography including cardiac function, morphology, strain and hemodynamic assessment. Results Left ventricular mass was higher in male than in female athletes (174 ± 44 vs. 141 ± 36g,p< 0.01) due to greater end-diastolic intraventricular septal, LV posterior wall and LV basal diameter. However, LV mass index did not differ between the groups. End-diastolic LV volume and right ventricular area, both indexed to body-surface-area, were greater in men than in women (52.8 ± 11.0 vs. 46.1 ± 8.5 ml/m2,p< 0.01, 9.5 ± 2.4 vs. 8.1 ± 1.7 cm2/m2,p< 0.01). In contrast, women had higher LV systolic global longitudinal strain (-20.2 ± 2.6 vs. -18.8 ± 2.6%,p< 0.01) and LV outflow tract flow velocity (75.1 ± 11.1 vs. 71.2 ± 11.1 cm/s,p= 0.04). Systolic and diastolic blood pressure, LV ejection fraction, and stroke volume index were not different between sexes. Conclusion Cardiac sex differences are present even among masters athletes. Lifelong exercise training does not appear to exasperate morphological difference to a point of cardiac risk or dysfunction in both male and female athletes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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) | 0.002 | 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".