Prevalence of abnormal ECG findings among female brazilian football players of different ethnicities and their association with imaging results
Bibliographic record
Abstract
Abstract Background Gender and ethnicity are important determinants of abnormal ECG findings in athletes. However, data on the prevalence of these abnormalities and their association with imaging results in female Brazilian football players (FBFP) from different ethnic backgrounds remain limited. Objective To evaluate the prevalence of abnormal ECG findings and their association with imaging results in FBFP. Methods This multicenter observational study included FBFP who underwent pre-participation evaluations between January 2010 and October 2024. The sample comprised 994 FBFP aged 15–35 years (315 white, 330 mixed-race, and 349 black) from 28 elite professional clubs across Brazil’s five geographic regions (11 states and 14 cities). Athletes with abnormal ECG findings underwent further investigation, including transthoracic echocardiography (TTE). Cardiac magnetic resonance (CMR) was performed based on TTE results or clinical suspicion. Results A total of 29 (2.9%) athletes had abnormal ECGs, and 28 (96%) of these showed normal TTE results. In the entire sample, the prevalence of T-wave inversion in leads II + aVF, V5, and V6 was 0.9%, 1.0%, and 0.6%, respectively, with no ethnic differences. Two FBFP (0.2%; one mixed-race and one black) exhibited Wolff-Parkinson-White pattern, and four others (0.4%; two white and two black) showed ST-segment depression. The black athlete with ST-segment depression also presented inferolateral T-wave inversion, and an abnormal TTE revealed reduced left ventricular global longitudinal strain in the inferior, lateral, and anterior apical segments. CMR imaging confirmed apical hypertrophic cardiomyopathy. Conclusion In this large, ethnically diverse sample of FBFP, we found a low prevalence of abnormal ECG findings. Although rare, inferolateral T-wave inversion may be associated with structural cardiac disease.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".