Three-Dimensional-Derived Echocardiographic Left Ventricular Structure and Function and Indices from the 12-Lead Electrocardiogram across the Menstrual Cycle in Healthy Physically Active Females: An Exploratory Study
Bibliographic record
Abstract
Background: The impact of the menstrual phases on left ventricular (LV) structure and function using 3D echocardiography and resting electrocardiogram (ECG) in healthy, eumenorrheic, and physically active females has not been investigated. Methods: sixteen females (20 y ± 2) underwent 3D echocardiography and an ECG at three time points in the menstrual cycle phases (follicular, ovulation, luteal). LV end-diastolic volume (LVEDVi), LV ejection fraction (LVEF), LV mass allometrically indexed to height2.7 (LVMi), torsion, and global longitudinal, circumferential, and radial strain (GLS, GCS, and GRS) were evaluated. ECG data of the P and QRS waves were presented as well as axis deviation, chamber enlargement, and any rhythm abnormalities. Results: LVMi was significantly higher in the luteal phase (36.4 g/m2.7 ± 3.3) compared to the follicular (35.0 g/m2.7 ± 3.7) and ovulation (34.7 g/m2.7 ± 4.3) phases (p = 0.026). There were no differences in other indices of LV structure and function or ECG variables across all phases of the menstrual cycle or evidence of arrhythmia. Conclusions: In physically active females, there is a small but significantly higher LVMi associated with the luteal phase of the menstrual cycle with no concomitant change in LV function or ECG parameters. These findings are important to consider when conducting clinical or research serial assessments.
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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) | 0.001 | 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".