Evidence map›Paper›PMID 42277326›Full record

ArticleNPJ digital medicine2026

A systematic review of explainable artificial intelligence and cardiac electrophysiological models addressing sports-related sudden cardiac death and arrest in adolescents and young adults.

Erik Vanegas Müller, Nicharee Srikijkasemwat, Andrew Gan, Betty Raman, Mirae Harford, Liang He, Abhirup Banerjee, Katja Gehmlich, Paul Leeson, Mauricio Villarroel

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Article in NPJ digital medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Erik Vanegas MüllerThe Podium Institute for Sports Medicine and Technology, Department of Engineering Science, University of Oxford, Oxford, UK. erik.vanegasmuller@eng.ox.ac.uk.
Nicharee SrikijkasemwatInstitute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK.
Andrew GanDepartment of Cardiovascular Sciences, University of Birmingham, Birmingham, UK.
Betty RamanDivision of Cardiovascular Medicine, Radcliffe Department of Medicine, and British Heart Foundation Centre of Research Excellence Oxford, University of Oxford, Oxford, UK.
Mirae HarfordInstitute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK.
Liang HeThe Podium Institute for Sports Medicine and Technology, Department of Engineering Science, University of Oxford, Oxford, UK.
Abhirup BanerjeeInstitute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK.
Katja GehmlichDepartment of Cardiovascular Sciences, University of Birmingham, Birmingham, UK.
Paul LeesonDivision of Cardiovascular Medicine, Radcliffe Department of Medicine, and British Heart Foundation Centre of Research Excellence Oxford, University of Oxford, Oxford, UK.
Mauricio VillarroelThe Podium Institute for Sports Medicine and Technology, Department of Engineering Science, University of Oxford, Oxford, UK. mauricio.villarroel@eng.ox.ac.uk.

Funding

British Heart Foundation IA/F/23/275037Royal Society University Research Fellowship URFR1314
6 · The paper itself

Abstract

Sudden Cardiac Death (SCD) is a fatal event occurring within one hour of a witnessed or 24 hours of an unwitnessed Sudden Cardiac Arrest (SCA), being the leading medical cause of death among adolescent and young adult athletes. We examined the epidemiology of sports-related SCD (SrSCD) and SCA (SrSCA) incidence in adolescents and young adults, explainable Artificial Intelligence (xAI) applied to life-threatening arrhythmias, and cardiac electrophysiological models. We systematically searched peer-reviewed studies from eight databases between 2013-2025 (PROSPERO: CRD42024565960), using PROBAST for bias assessment. From 9574 studies, we included 84 (incidence: 16, xAI: 30, modelling: 38). SrSCD incidence ranged from 0.1 to 0.6 per 100,000 participants per year. Gradient-weighted Class Activation Mapping dominated as xAI technique. Cardiac electrophysiological models predominantly focused on cellular and tissue-level electrophysiology. We advocate for standardised SrSCD/SrSCA definitions and integration of epidemiological risk factors with xAI and cardiac modelling frameworks to advance athlete-specific risk stratification.

Identifiers

PMID42277326
PMCPMC13601518

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.