Identifying risk patterns for sudden cardiac death in athletes: A clustering and principal component analysis approach
Giacinto Angelo Sgarro,
Paride Vasco,
Domenico Santoro,
Luca Grilli,
Marco Giglio,
Natale Daniele Brunetti,
Luigi Traetta,
Giuseppe Cibelli and
Anna Antonia Valenzano
PLOS ONE, 2026, vol. 21, issue 1, 1-27
Abstract:
Sudden Cardiac Death (SCD) is a critical and unexpected condition that occurs due to cardiac causes within one hour of the onset of acute cardiovascular symptoms or twenty-four hours in unwitnessed cases. Despite advancements in cardiovascular medicine, practical methods for predicting SCD are still lacking, and there are no standardized systems to identify individuals at risk, especially in seemingly healthy populations such as athletes. In this study, we employed hierarchical clustering and principal component analysis (PCA) on data from 711 competitive athletes, revealing distinct patterns and cluster distributions in PCA space. Specifically, Clustering revealed characteristic feature combinations associated with increased SCD risk in athletes. Notably, certain clusters shared traits, including participation in Class C sports, sinus tachycardia, ventricular pre-excitation, personal or family history of heart disease, T-wave inversions, and prolonged QTc intervals. PCA helped visualize these patterns in distinct spatial regions, highlighting underlying structures and aiding intuitive risk interpretation. These results enable scientists to derive cluster metrics that serve as reference points for classifying new individuals and visually representing risk patterns in a clear graphical format. These findings establish a foundation for predictive tools that, with additional clinical validation, could aid in the prevention of SCD. The dataset used in this study, along with the clustering and PCA results, is available to the scientific community in an open format, together with the necessary tools and scripts to enable independent experimentation and further analysis.
Date: 2026
References: View complete reference list from CitEc
Citations:
Downloads: (external link)
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0339377 (text/html)
https://journals.plos.org/plosone/article/file?id= ... 39377&type=printable (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0339377
DOI: 10.1371/journal.pone.0339377
Access Statistics for this article
More articles in PLOS ONE from Public Library of Science
Bibliographic data for series maintained by plosone ().