scholarly journals Data-driven clustering supports adaptive remodeling of athlete's hearts: An echocardiographic study from the Taipei Summer Universiade

Author(s):  
Kuan-Chih Huang ◽  
Chang-En Lin ◽  
Lian-Yu Lin ◽  
Juey-Jen Hwang ◽  
Lung-Chun Lin
2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
K Huang

Abstract Background Sport-specific adaptations of the athlete's heart are still under investigation. This study sought to provide a proof-of-concept for hierarchical clustering of echocardiography-derived parameters in unfolding the adaptations and to make a comparison between hypothesis-driven and data-driven approaches for characterizing the athlete's heart. Methods Anthropometric, echocardiographic and electrocardiographic assessments were collected during the peri-participation cardiovascular examination of 2017 Summer Universiade. Besides standard echocardiography and strain measurements, ventricular-arterial coupling was assessed by the ratio of effective arterial elastance (Ea) to left ventricular end-systolic elastance (Ees), using a modified single-beat algorithm to calculate Ees. Results A total of 598 elite athletes (348 male, mean age 23±2.5 years) engaged 24 disciplines were grouped by Mitchell's classification. The hypothesis-driven approach showed significant differences in heart rate, ventricular size, and stroke volume when classified by dynamic levels. Adaptations of ventricular function were not found. Contrarily, the data-driven approach not only hierarchically clustered athletes with more manifest morphologic remodeling, more proportions playing high dynamic sports but also showed a functional propensity of lower Ea and Ees, supranormal diastolic function and preserved ventricular-arterial coupling with ample pumping reserve. Phenotype heatmaps of athletes Conclusions The hierarchical clustering can analyze numerous echocardiography-derived phenotypes pertaining to an individual athlete as well as discern an adaptive propensity of the athlete's heart to be the resting status of a reservoir-rich pump. This pilot demonstration of the data-driven approach in figuring out integrated physiologic adaptations with remodeling-relevant geometry and function leads to a fundamentally improved understanding of the athlete's heart and then will be applicable to various domains.


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