Sport-specific allometric scaling equations incorporating height, sex, heart rate, and discipline predicted LV structure (R²=0.47-0.59), whereas 69.6% exceeded standard BSA thresholds for LVEDVi.
Cross-Sectional (n=181)
Does allometric scaling improve the prediction accuracy of left ventricular structural parameters compared to conventional BSA indexing in elite cyclists?
Sport-specific allometric scaling equations using height, sex, heart rate, and discipline provide superior prediction of normal left ventricular dimensions in elite cyclists compared to standard BSA indexing, potentially reducing unnecessary investigations.
Abstract Introduction The athlete's heart demonstrates complex remodelling with variation by sex, sport, and body size. Current guidelines recommend standard linear scaling of cardiac parameters to body surface area (BSA), yet this inadequately accounts for allometric relationships. Elite athletes will often exceed conventional thresholds of left ventricular (LV) size using standard scaling, potentially leading to unnecessary onward investigation. Sport-specific prediction equations incorporating allometric scaling could improve diagnostic accuracy in pre-participation cardiac screening (PPCS) of competitive cyclists. Purpose To develop allometric scaling equations for LV structural parameters in elite cyclists, accounting for body size, sex, discipline, and heart rate, and to compare with conventional BSA indexing. Methods We evaluated 181 elite cyclists (96% white British ethnicity) with a normal PPCS (105 males, 76 females; age 22.7±5.5 years; discipline 128 endurance, 53 sprint) to develop sport-specific prediction equations. Comprehensive echocardiography was performed. Weighted least squares allometric regression was used to determine optimal scaling exponents for height, mass, and BSA. Statistical models were evaluated, advancing to more complex models only when they significantly improved prediction accuracy. For each parameter, equations were developed to predict expected values and calculate z-scores using piecewise linear regression on ln(pp). Results Males had larger standard scaled LV dimensions than females (LVEDVi: 81.7±13.3 vs. 70.3±11.3 ml/m2; LVMi: 95.4±19.7 vs 79.5±12.6 g/m2, both p0.001). Using ASE 2015 guidelines, 69.6% exceeded thresholds for LVEDVi, 62.9% for LVESVi and 14.9% for LVMi. Allometric scaling with height provided superior fit, with a stronger coefficient than either mass or BSA. RR interval, reflecting variability in resting heart rate and discipline focus emerged as important determinants and were incorporated into the models. Prediction equations: LVEDV=47.5×Height1.7×1.15(if male)×1.09 (if endurance) R²=0.59; LVESV=19.4×Height1.7×1.19(if male)×1.05(if endurance) R²=0.47; LV mass=51.4×Height1.7×RR0.1×1.22(if male)×1.14(if endurance) R²=0.57. The prediction equations yield z-scores, and percentage predicted values for each measured parameter. Values falling within the 95% reference interval (2.5th-97.5thpercentiles) are classified as normal physiologic adaptation. Conclusions Allometric scaling with height provides superior indices of LV structure versus BSA indexing. Sport-specific equations accounting for height, sex, heart rate, and discipline offer improved diagnostic precision. Current guideline thresholds may be inappropriate for elite cyclists, and allometric scaling could reduce unnecessary further investigations.LVEDVFor image description, please refer to the figure legend and surrounding text. LVMFor image description, please refer to the figure legend and surrounding text.
Herrera et al. (Mon,) conducted a cross-sectional in Elite cyclists (n=181). Allometric scaling with height vs. Standard linear scaling to body surface area (BSA) was evaluated on Left ventricular structural parameters (LVEDV, LVESV, LV mass). Sport-specific allometric scaling equations incorporating height, sex, heart rate, and discipline predicted LV structure (R²=0.47-0.59), whereas 69.6% exceeded standard BSA thresholds for LVEDVi.