Predictive Effect of Echocardiographic Assessment of Myocardial Efficiency on Martial Arts Performance

Cardiac strain and myocardial work indices may provide additional information for performance stratification beyond traditional physiological assessments in martial arts, but their relevance to anaerobic and neuromotor performance remains insufficiently defined. This cross-sectional observational predictive modeling study assessed whether echocardiographic myocardial efficiency indices were associated with performance classification among national-level martial artists. A total of 180 athletes were assessed, and the primary comparative analysis used the top and bottom tertiles of a composite performance score to define higher-performance athletes and a lower-performance internal reference group, respectively, rather than a non-athlete control group. Echocardiographic indices included global longitudinal strain (GLS), global work efficiency (GWE), global wasted work (GWW), and myocardial performance index (MPI). Performance outcomes included Wingate anaerobic power, agility time, reaction time, Balance Error Scoring System (BESS) errors, and Finger-to-Nose Alternation Test (FTNAT) coordination. Higher-performance athletes showed greater peak power than the lower-performance reference group (11.7 ± 1.3 vs. 9.3 ± 1.2 W/kg, p = 0.002), faster agility time (9.0 ± 0.7 vs. 10.6 ± 0.9 s, p = 0.001), and higher technical execution scores (8.4 ± 1.0 vs. 5.6 ± 1.4, p = 0.001). GLS magnitude was greater across myocardial segments, GWE was higher (96.8% vs. 92.1%, p = 0.002), and GWW was lower (9.4% vs. 13.2%, p = 0.003). GLS and GWE were associated with group classification in regression models, while lower MPI values were associated with shorter agility times and fewer balance errors, indicating better performance direction for both outcomes. These findings suggest that cardiac strain and myocardial work indices are associated with anaerobic and neuromotor performance in martial artists; however, longitudinal validation is required before these measures can be considered predictive markers for talent identification or training decisions.