{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T16:14:59Z","timestamp":1790007299688,"version":"4.0.1"},"reference-count":41,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2025,8,28]],"date-time":"2025-08-28T00:00:00Z","timestamp":1756339200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":["heartrhythmopen.com","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Heart Rhythm O2"],"published-print":{"date-parts":[[2025,9]]},"DOI":"10.1016\/j.hroo.2025.08.040","type":"journal-article","created":{"date-parts":[[2025,9,2]],"date-time":"2025-09-02T06:43:46Z","timestamp":1756795426000},"update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":1,"title":["Artificial intelligence\u2013enhanced electrocardiography and sudden death risk factors in cardiac arrest survivors diagnosed with hypertrophic cardiomyopathy"],"prefix":"10.1016","author":[{"given":"William H.","family":"Swain","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John R.","family":"Giudicessi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jeffrey B.","family":"Geske","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Darrell B.","family":"Newman","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"J. Martijn","family":"Bos","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shahid","family":"Karim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peter A.","family":"Noseworthy","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zachi I.","family":"Attia","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Paul A.","family":"Friedman","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Adelaide M.","family":"Arruda-Olson","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael J.","family":"Ackerman","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Steve R.","family":"Ommen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6658-0971","authenticated-orcid":false,"given":"Konstantinos C.","family":"Siontis","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.hroo.2025.08.040_bib1","doi-asserted-by":"crossref","first-page":"e159","DOI":"10.1016\/j.jacc.2020.08.045","article-title":"AHA\/ACC Guideline for the diagnosis and treatment of patients with hypertrophic cardiomyopathy: a report of the American College of Cardiology\/American Heart Association Joint Committee on Clinical Practice Guidelines","volume":"76","author":"Ommen","year":"2020","journal-title":"J Am Coll Cardiol"},{"key":"10.1016\/j.hroo.2025.08.040_bib2","doi-asserted-by":"crossref","first-page":"1249","DOI":"10.1016\/j.jacc.2015.01.019","article-title":"New perspectives on the prevalence of hypertrophic cardiomyopathy","volume":"65","author":"Semsarian","year":"2015","journal-title":"J Am Coll Cardiol"},{"key":"10.1016\/j.hroo.2025.08.040_bib3","doi-asserted-by":"crossref","first-page":"1387","DOI":"10.1161\/CIRCULATIONAHA.117.033200","article-title":"Genotype and lifetime burden of disease in hypertrophic cardiomyopathy: insights from the Sarcomeric Human Cardiomyopathy Registry (SHaRe)","volume":"138","author":"Ho","year":"2018","journal-title":"Circulation"},{"key":"10.1016\/j.hroo.2025.08.040_bib4","doi-asserted-by":"crossref","first-page":"198","DOI":"10.1161\/CIRCEP.113.001376","article-title":"Pathogeneses of sudden cardiac death in National Collegiate Athletic Association athletes","volume":"7","author":"Harmon","year":"2014","journal-title":"Circ Arrhythm Electrophysiol"},{"key":"10.1016\/j.hroo.2025.08.040_bib5","doi-asserted-by":"crossref","first-page":"1085","DOI":"10.1161\/CIRCULATIONAHA.108.804617","article-title":"Sudden deaths in young competitive athletes: analysis of 1866 deaths in the United States, 1980\u20132006","volume":"119","author":"Maron","year":"2009","journal-title":"Circulation"},{"key":"10.1016\/j.hroo.2025.08.040_bib6","doi-asserted-by":"crossref","first-page":"1706","DOI":"10.1161\/CIRCULATIONAHA.119.040271","article-title":"Hypertrophic cardiomyopathy-related sudden cardiac death in young people in Ontario","volume":"140","author":"Weissler-Snir","year":"2019","journal-title":"Circulation"},{"key":"10.1016\/j.hroo.2025.08.040_bib7","doi-asserted-by":"crossref","DOI":"10.1161\/CIRCEP.124.012970","article-title":"Resuscitated sudden cardiac arrest as the initial presentation of hypertrophic cardiomyopathy","volume":"17","author":"Swain","year":"2024","journal-title":"Circ Arrhythm Electrophysiol"},{"key":"10.1016\/j.hroo.2025.08.040_bib8","doi-asserted-by":"crossref","first-page":"722","DOI":"10.1016\/j.jacc.2019.12.030","article-title":"Detection of hypertrophic cardiomyopathy using a convolutional neural network-enabled electrocardiogram","volume":"75","author":"Ko","year":"2020","journal-title":"J Am Coll Cardiol"},{"key":"10.1016\/j.hroo.2025.08.040_bib9","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1016\/j.ijcard.2021.08.026","article-title":"Detection of hypertrophic cardiomyopathy by an artificial intelligence electrocardiogram in children and adolescents","volume":"340","author":"Siontis","year":"2021","journal-title":"Int J Cardiol"},{"key":"10.1016\/j.hroo.2025.08.040_bib10","doi-asserted-by":"crossref","first-page":"416","DOI":"10.1093\/ehjdh\/ztae029","article-title":"Hypertrophic cardiomyopathy detection with artificial intelligence electrocardiography in international cohorts: an external validation study","volume":"5","author":"Siontis","year":"2024","journal-title":"Eur Heart J Digit Health"},{"key":"10.1016\/j.hroo.2025.08.040_bib11","doi-asserted-by":"crossref","DOI":"10.1056\/AIoa2400421","article-title":"Calibration of ECG-based deep-learning algorithm scores for patients flagged as high risk for hypertrophic cardiomyopathy","volume":"2","author":"Lampert","year":"2025","journal-title":"NEJM AI"},{"key":"10.1016\/j.hroo.2025.08.040_bib12","doi-asserted-by":"crossref","first-page":"2010","DOI":"10.1093\/eurheartj\/eht439","article-title":"A novel clinical risk prediction model for sudden cardiac death in hypertrophic cardiomyopathy (HCM risk-SCD)","volume":"35","author":"O\u2019Mahony","year":"2014","journal-title":"Eur Heart J"},{"key":"10.1016\/j.hroo.2025.08.040_bib13","doi-asserted-by":"crossref","first-page":"3503","DOI":"10.1093\/eurheartj\/ehad194","article-title":"2023 ESC Guidelines for the management of cardiomyopathies","volume":"44","author":"Abrelo","year":"2023","journal-title":"Eur Heart J"},{"key":"10.1016\/j.hroo.2025.08.040_bib14","doi-asserted-by":"crossref","first-page":"1462","DOI":"10.1016\/j.hrthm.2019.04.040","article-title":"Risk factors for lethal arrhythmic events in children and adolescents with hypertrophic cardiomyopathy and an implantable defibrillator: an international multicenter study","volume":"16","author":"Balaji","year":"2019","journal-title":"Heart Rhythm"},{"key":"10.1016\/j.hroo.2025.08.040_bib15","doi-asserted-by":"crossref","first-page":"1915","DOI":"10.1016\/j.jacc.2015.02.061","article-title":"Hypertrophic cardiomyopathy in adulthood associated with low cardiovascular mortality with contemporary management strategies","volume":"65","author":"Maron","year":"2015","journal-title":"J Am Coll Cardiol"},{"key":"10.1016\/j.hroo.2025.08.040_bib16","doi-asserted-by":"crossref","first-page":"644","DOI":"10.1001\/jamacardio.2019.1391","article-title":"Enhanced American College of Cardiology\/American Heart Association strategy for prevention of sudden cardiac death in high-risk patients with hypertrophic cardiomyopathy","volume":"4","author":"Maron","year":"2019","journal-title":"JAMA Cardiol"},{"key":"10.1016\/j.hroo.2025.08.040_bib17","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/j.pcad.2023.08.005","article-title":"Art and science of risk stratification of sudden cardiac death in hypertrophic cardiomyopathy: current state, unknowns, and future directions","volume":"80","author":"Siontis","year":"2023","journal-title":"Prog Cardiovasc Dis"},{"key":"10.1016\/j.hroo.2025.08.040_bib18","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1161\/CIRCULATIONAHA.120.051968","article-title":"Gaps in evidence for risk stratification for sudden cardiac death in hypertrophic cardiomyopathy","volume":"143","author":"Pelliccia","year":"2021","journal-title":"Circulation"},{"key":"10.1016\/j.hroo.2025.08.040_bib19","doi-asserted-by":"crossref","DOI":"10.1161\/CIRCGEN.120.002930","article-title":"Revisiting the diagnostic yield of hypertrophic cardiomyopathy genetic testing","volume":"13","author":"Butters","year":"2020","journal-title":"Circ Genom Precis Med"},{"key":"10.1016\/j.hroo.2025.08.040_bib20","doi-asserted-by":"crossref","first-page":"1479","DOI":"10.1016\/j.jacc.2014.05.006","volume":"64","author":"Maron","year":"2014","journal-title":"J Am Coll Cardiol"},{"key":"10.1016\/j.hroo.2025.08.040_bib21","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1016\/j.jacc.2009.02.071","article-title":"Outcome of patients with hypertrophic cardiomyopathy and a normal electrocardiogram","volume":"54","author":"McLeod","year":"2009","journal-title":"J Am Coll Cardiol"},{"key":"10.1016\/j.hroo.2025.08.040_bib22","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1016\/j.hrthm.2019.07.019","article-title":"The electrocardiogram in the diagnosis and management of patients with hypertrophic cardiomyopathy","volume":"17","author":"Finocchiaro","year":"2020","journal-title":"Heart Rhythm"},{"key":"10.1016\/j.hroo.2025.08.040_bib23","doi-asserted-by":"crossref","first-page":"286","DOI":"10.1016\/j.jelectrocard.2023.07.002","article-title":"Saliency maps provide insights into artificial intelligence-based electrocardiography models for detecting hypertrophic cardiomyopathy","volume":"81","author":"Siontis","year":"2023","journal-title":"J Electrocardiol"},{"key":"10.1016\/j.hroo.2025.08.040_bib24","doi-asserted-by":"crossref","DOI":"10.1161\/CIRCHEARTFAILURE.124.012667","article-title":"Detection of hypertrophic cardiomyopathy on electrocardiogram using artificial intelligence","volume":"18","author":"Hillis","year":"2025","journal-title":"Circ Heart Fail"},{"key":"10.1016\/j.hroo.2025.08.040_bib25","doi-asserted-by":"crossref","DOI":"10.1136\/heartjnl-2024-325608","article-title":"Clinical implementation of an AI-enabled ECG for hypertrophic cardiomyopathy detection","author":"Love","year":"2025","journal-title":"Heart"},{"key":"10.1016\/j.hroo.2025.08.040_bib26","doi-asserted-by":"crossref","first-page":"1324","DOI":"10.1016\/j.jacep.2025.02.024","article-title":"Real-world artificial intelligence\u2013based electrocardiographic analysis to diagnose hypertrophic cardiomyopathy","volume":"11","author":"Desai","year":"2025","journal-title":"JACC Clin Electrophysiol"},{"key":"10.1016\/j.hroo.2025.08.040_bib27","doi-asserted-by":"crossref","DOI":"10.1161\/CIRCOUTCOMES.118.005289","article-title":"Automated and interpretable patient ECG profiles for disease detection, tracking, and discovery","volume":"12","author":"Tison","year":"2019","journal-title":"Circ Cardiovasc Qual Outcomes"},{"key":"10.1016\/j.hroo.2025.08.040_bib28","article-title":"Identification of patients with dilated phase of hypertrophic cardiomyopathy using a convolutional neural network applied to multiple, dual, and single lead electrocardiogram","volume":"46","author":"Hirota","year":"2023","journal-title":"Int J Cardiol Heart Vasc"},{"key":"10.1016\/j.hroo.2025.08.040_bib29","doi-asserted-by":"crossref","first-page":"524","DOI":"10.1007\/s00380-024-02367-9","article-title":"Evaluating convolutional neural network-enhanced electrocardiography for hypertrophic cardiomyopathy detection in a specialized cardiovascular setting","volume":"39","author":"Hirota","year":"2024","journal-title":"Heart Vessels"},{"key":"10.1016\/j.hroo.2025.08.040_bib30","doi-asserted-by":"crossref","DOI":"10.1016\/j.jelectrocard.2025.153888","article-title":"A systematic review and meta-analysis on the performance of convolutional neural networks ECGs in the diagnosis of hypertrophic cardiomyopathy","volume":"89","author":"Queiroz","year":"2025","journal-title":"J Electrocardiol"},{"key":"10.1016\/j.hroo.2025.08.040_bib31","doi-asserted-by":"crossref","first-page":"991","DOI":"10.1038\/s44161-025-00685-3","article-title":"Identification of hypertrophic cardiomyopathy on electrocardiographic images with deep learning","volume":"4","author":"Sangha","year":"2025","journal-title":"Nat Cardiovasc Res"},{"key":"10.1016\/j.hroo.2025.08.040_bib32","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1016\/j.cvdhj.2022.10.002","article-title":"Tandem deep learning and logistic regression models to optimize hypertrophic cardiomyopathy detection in routine clinical practice","volume":"3","author":"Maanja","year":"2022","journal-title":"Cardiovasc Digit Health J"},{"key":"10.1016\/j.hroo.2025.08.040_bib33","doi-asserted-by":"crossref","DOI":"10.3389\/fcvm.2022.889523","article-title":"Derivation and validation of a screening model for hypertrophic cardiomyopathy based on electrocardiogram features","volume":"9","author":"Guo","year":"2022","journal-title":"Front Cardiovasc Med"},{"key":"10.1016\/j.hroo.2025.08.040_bib34","doi-asserted-by":"crossref","first-page":"755","DOI":"10.1161\/CIRCULATIONAHA.121.058696","article-title":"Multinational federated learning approach to train ECG and echocardiogram models for hypertrophic cardiomyopathy detection","volume":"146","author":"Goto","year":"2022","journal-title":"Circulation"},{"key":"10.1016\/j.hroo.2025.08.040_bib35","doi-asserted-by":"crossref","first-page":"126","DOI":"10.1016\/j.tcm.2024.08.002","article-title":"Artificial intelligence-driven electrocardiography: innovations in hypertrophic cardiomyopathy management","volume":"35","author":"Ordine","year":"2025","journal-title":"Trends Cardiovasc Med"},{"key":"10.1016\/j.hroo.2025.08.040_bib36","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1016\/j.amjcard.2024.11.028","article-title":"A multicenter evaluation of the impact of therapies on deep learning-based electrocardiographic hypertrophic cardiomyopathy markers","volume":"237","author":"Dhingra","year":"2025","journal-title":"Am J Cardiol"},{"key":"10.1016\/j.hroo.2025.08.040_bib37","doi-asserted-by":"crossref","DOI":"10.1016\/j.jacadv.2023.100582","article-title":"Patient-level artificial intelligence\u2013enhanced electrocardiography in hypertrophic cardiomyopathy: longitudinal treatment and clinical biomarker correlations","volume":"2","author":"Siontis","year":"2023","journal-title":"JACC Adv"},{"key":"10.1016\/j.hroo.2025.08.040_bib38","doi-asserted-by":"crossref","first-page":"1032","DOI":"10.1016\/j.jacc.2022.01.005","article-title":"Assessment of disease status and treatment response with artificial intelligence\u2013enhanced electrocardiography in obstructive hypertrophic cardiomyopathy","volume":"79","author":"Tison","year":"2022","journal-title":"J Am Coll Cardiol"},{"key":"10.1016\/j.hroo.2025.08.040_bib39","doi-asserted-by":"crossref","first-page":"1390","DOI":"10.1016\/j.hrthm.2024.01.031","article-title":"Identification of high-risk imaging features in hypertrophic cardiomyopathy using electrocardiography: a deep-learning approach","volume":"21","author":"Carrick","year":"2024","journal-title":"Heart Rhythm"},{"key":"10.1016\/j.hroo.2025.08.040_bib40","doi-asserted-by":"crossref","DOI":"10.1016\/j.compbiomed.2022.105325","article-title":"A transformer-based deep neural network for arrhythmia detection using continuous ECG signals","volume":"144","author":"Hu","year":"2022","journal-title":"Comput Biol Med"},{"key":"10.1016\/j.hroo.2025.08.040_bib41","article-title":"Foundation model of ECG diagnosis: diagnostics and explanations of any form and rhythm on ECG","volume":"5","author":"Tian","year":"2024","journal-title":"Cell Rep Med"}],"container-title":["Heart Rhythm O2"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2666501825004180?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2666501825004180?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,9,27]],"date-time":"2025-09-27T06:45:50Z","timestamp":1758955550000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S2666501825004180"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9]]},"references-count":41,"alternative-id":["S2666501825004180"],"URL":"https:\/\/doi.org\/10.1016\/j.hroo.2025.08.040","relation":{},"ISSN":["2666-5018"],"issn-type":[{"value":"2666-5018","type":"print"}],"subject":[],"published":{"date-parts":[[2025,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Artificial intelligence\u2013enhanced electrocardiography and sudden death risk factors in cardiac arrest survivors diagnosed with hypertrophic cardiomyopathy","name":"articletitle","label":"Article Title"},{"value":"Heart Rhythm O2","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.hroo.2025.08.040","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 Heart Rhythm Society. Published by Elsevier Inc.","name":"copyright","label":"Copyright"}]}}