Gender influence on the adaptation of atrial performance to training
Bibliographic record
Abstract
Abstract Background: High‐intensity training has been associated with atrial remodelling and arrhythmias in men. Our purpose was to analyse atrial performance in female endurance athletes, compared to male athletes and controls. Methods: This was a cross‐sectional study. We included four groups: female athletes, females controls, male athletes and male controls. Left (LA) and right atrial (RA) volumes and function were assessed using 2D and speckle‐tracking echocardiography to determine peak atrial strain‐rate at atrial (SRa) and ventricular contraction (SRs), as surrogates of atrial contractile and reservoir function, respectively. ANOVA and Bonferroni's statistical tests were used to compare variables among groups. Results: We included 82 subjects, 39 women (19 endurance athletes, 20 controls) and 43 men (22 endurance athletes, 21 controls). Mean age was similar between groups (36.6 ± 5.6 years). Athletes had larger bi‐atrial volumes, compared to controls (women, LA 27.1 vs. 15.8 ml/m2, p < 0.001; RA 22.31 vs. 14.2 ml/m2, p = 0.009; men, LA: 25.0 vs. 18.5 ml/m2, p = 0.003; RA 30.8 vs. 21.9 ml/m2, p < 0.001) and lower strain‐rate (women, LASRa −1.60 vs. −2.18 s−1, p < 0.001; RASRa −1.89 vs. −2.38 s−1, p = 0.009; men, LASRa −1.21 vs. −1.44 s−1, p = 1; RASRa −1.44 vs. −1.60 s−1, p = 1). However, RA indexed size was lower and bi‐atrial deformation greater in female athletes, compared to male athletes. Conclusions: The atria of both male and female athletes shows specific remodelling, compared to sedentary subjects, with larger size and less deformation at rest, particularly for the RA. Despite a similar extent of remodelling, the pattern in women had greater bi‐atrial myocardial deformation and smaller RA size.
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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".