Key result
ESC and AHA/ACC sport classifications capture population-level cardiac remodelling but cannot reliably predict individual cardiac phenotypes (balanced accuracy 34.2% and 37.7%).
Why the study?
Sport-type classification frameworks recommended by ESC and AHA/ACC guidelines are used to contextualize athletic cardiac remodelling but remain unvalidated against CMR phenotypes.
Do ESC and AHA/ACC sport classifications reliably predict individual CMR-determined cardiac remodelling phenotypes in elite athletes?
Cross-Sectional (n=1,024)
Do ESC and AHA/ACC sport classifications reliably predict individual CMR-determined cardiac remodelling phenotypes in elite athletes?
Odds Ratio: 3.82
p-value: p=<0.001
Current ESC and AHA/ACC sport-type classification frameworks do not reliably predict individual cardiac phenotypes in elite athletes, suggesting clinical interpretation should prioritize observed CMR mass-volume relationships over sport type.
Captured external expert commentary on this paper, strongest first. Original sources are linked where available.
“Bij sporters is vaak de vraag of een afwijkende vorm van het hart door het sporten komt, of door ziekte. Dit onderzoek laat zien dat het risico's geeft als artsen alleen het sporttype gebruiken om het sportershart te beoordelen.”
Classification frameworks poorly discriminate individual CMR phenotypes; challenges consensus but leaves open need for prospective validation before practice change.
Aims : Sport-type classification frameworks recommended by European (ESC) and American (AHA/ACC) guidelines are used to contextualize cardiac remodelling in athletes but remain unvalidated against cardiac magnetic resonance (CMR) phenotypes. We aimed to evaluate whether sport classifications predict CMR-determined cardiac remodelling phenotypes in elite athletes. Methods and Results : We included 1,024 individuals: 775 elite athletes (310 women, 48 disciplines) and 249 controls. Athletes were classified by the ESC (four-category) and AHA/ACC (static–dynamic, four-quadrant) frameworks. CMR metrics were transformed to sex-specific z-scores (remodelling: z≥1.645). Because no CMR convention defines geometric phenotypes in athletes, the most strongly associated CMR metric was used to define each framework's assumed phenotype. Performance was evaluated at population (R2) and individual (balanced accuracy) levels. ESC categories were most strongly associated with RVEDV (R2=0.170); RV remodelling prevalence increased from skill to endurance (8.3%–62.2%; OR 3.82 per category; P<0.001). The AHA/ACC static component was most strongly associated with LV mass (R2=0.077) and the dynamic component with RVEDV (R2=0.072). Individual-level discrimination was poor: balanced accuracy was 34.2% (ESC) and 37.7% (AHA/ACC) (vs 25% chance). LV mass and RVEDV showed coupled increases (R2=0.23), with 67% of athletes demonstrating concordant patterns rather than discrete static or dynamic phenotypes. Misclassification was most pronounced for predominantly high-static athletes, of whom 73.8% showed normal geometry rather than expected LV hypertrophy (17.5%). Conclusions : ESC and AHA/ACC sport classifications capture population-level remodelling but cannot reliably be used to predict individual cardiac phenotypes. In individual athletes interpretation should prioritise observed mass-volume relationships and the overall clinical context rather than sport type alone.
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Diepen et al. (2026) conducted a cross-sectional in Cardiac remodelling in elite athletes (n=1,024). ESC and AHA/ACC sport-type classification frameworks vs. Other sport categories / Controls was evaluated on CMR-determined cardiac remodelling phenotypes (OR 3.82, p=<0.001). ESC and AHA/ACC sport classifications capture population-level cardiac remodelling but cannot reliably predict individual cardiac phenotypes (balanced accuracy 34.2% and 37.7%).
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