Defining the Normal Spectrum of Electrocardiographic and Left Ventricular Adaptations in Mixed-Race Male Adolescent Soccer Players
Bibliographic record
Abstract
Background: Cardiovascular adaptation in adolescent athletes is significantly understudied compared with adult athletes. Among adult and adolescent black athletes (African or Afro Caribbean origin) electrical and left ventricular adaptation may overlap with morphologically mild hypertrophic cardiomyopathy (HCM). Adolescent mixed-race athletes, where one parent is white and the other is black, are the fastest growing ethnic group of athletes in the Western world, yet the electrical and structural manifestations in this cohort have never been described. The aim of our study was to examine the similarities and differences in the spectrum of ECG changes and left ventricular dimensions in a large cohort of healthy mixed-race adolescent soccer players compared with identical cohorts of white and black adolescent athletes. Methodology: 3000 healthy male soccer players (mean age 16.4±1.3 years) including an equal proportion of mixed-race, white and black athletes were evaluated with an ECG and echocardiogram. Results: Mixed-race athletes demonstrated a higher prevalence of T-wave inversion (8.6% vs. 2.3%; p<0.0001), a greater magnitude of left ventricular (LV) wall thickness (9.8 vs 9.2 mm; p<0.0001) and a smaller LV cavity (51.1 vs. 52.4 mm; p<0.0001) compared with white athletes. Mixed-race athletes demonstrated a lower prevalence of T-wave inversion (8.8% vs 12.6%; p<0.0001) and a smaller magnitude of LV wall thickness (9.8 vs. 10.1 mm; p<0.0001) compared with black athletes but revealed a larger LV cavity (51.1 vs. 50.6mm; p=0.005). 7% of mixed-race athletes either had a left ventricular wall thickness >12mm or inferior/ lateral T-wave inversion but did not reveal any overt phenotypic features of HCM during further investigation, compared with <2% white athletes. Conclusions: Mixed-race adolescent athletes show a higher prevalence of T-wave inversion and a greater magnitude of LV wall thickness compared with white athletes, but to a lesser extent than in black athletes. As with black athletes, a small but significant proportion of mixed-race athletes reveal electrical and structural features that would raise suspicion of HCM in a white athlete. Such variations among mixed-race athletes should be considered when evaluating this fast-growing ethnic group.
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) | 0.001 | 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".