{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,7]],"date-time":"2026-11-07T14:31:35Z","timestamp":1794061895881,"version":"4.8.0"},"reference-count":32,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2022,4,8]],"date-time":"2022-04-08T00:00:00Z","timestamp":1649376000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100008005","name":"Yonsei University College of Medicine","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100008005","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Cardiovasc. Med."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>The identification of latent atrial fibrillation (AF) in patients with ischemic stroke (IS) attributed to noncardioembolic etiology may have therapeutic implications. An artificial intelligence (AI) model identifying the electrocardiographic signature of AF present during normal sinus rhythm (NSR; AI-ECG-AF) can identify individuals with a high likelihood of paroxysmal AF (PAF) with NSR electrocardiogram (ECG).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>Using AI-ECG-AF, we aimed to compare the PAF risk between noncardioembolic IS subgroups and general patients of a university hospital after controlling for confounders. Further, we sought to compare the risk of PAF among noncardioembolic IS subgroups.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>After training AI-ECG-AF with ECG data of university hospital patients, model inference outputs were obtained for the control group (i.e., general patient population) and NSRs of noncardioembolic IS patients. We conducted multiple linear regression (MLiR) and multiple logistic regression (MLoR) analyses with inference outputs (for MLiR) or their binary form (set at threshold = 0.5 for MLoR) used as dependent variables and patient subgroups and potential confounders (age and sex) set as independent variables.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The number of NSRs inferenced for the control group, cryptogenic, large artery atherosclerosis (LAA), and small artery occlusion (SAO) strokes were 133,340, 133, 276, and 290, respectively. The regression analyses indicated that patients with noncardioembolic IS had a higher PAF risk based on AI-ECG-AF relative to the control group, after controlling for confounders with the \u201ccryptogenic\u201d subgroup having the highest risk (odds ratio [OR] = 1.974, 95% confidence interval [CI]: 1.371\u20132.863) followed by the \u201cLAA\u201d (OR = 1.592, 95% CI: 1.238\u20132.056) and \u201cSAO\u201d subgroups (OR = 1.400, 95% CI: 1.101\u20131.782). Subsequent regression analyses failed to illustrate the differences in PAF risk based on AI-ECG-AF among noncardioembolic IS subgroups.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Using AI-ECG-AF, we found that noncardioembolic IS patients had a higher PAF risk relative to the general patient population. The results from our study imply the need for more vigorous cardiac monitoring in noncardioembolic IS patients. AI-ECG-AF can be a cost-effective screening tool to identify high-risk noncardioembolic IS patients of PAF on-the-spot to be candidates for receiving additional prolonged cardiac monitoring. Our study highlights the potential of AI in clinical practice.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fcvm.2022.865852","type":"journal-article","created":{"date-parts":[[2022,4,8]],"date-time":"2022-04-08T02:35:56Z","timestamp":1649385356000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":9,"title":["Evaluating the Risk of Paroxysmal Atrial Fibrillation in Noncardioembolic Ischemic Stroke Using Artificial Intelligence-Enabled ECG Algorithm"],"prefix":"10.3389","volume":"9","author":[{"given":"Changho","family":"Han","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Oyeon","family":"Kwon","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mineok","family":"Chang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sunghoon","family":"Joo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yeha","family":"Lee","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jin Soo","family":"Lee","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ji Man","family":"Hong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Seong-Joon","family":"Lee","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dukyong","family":"Yoon","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2022,4,8]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"983","DOI":"10.1161\/01.STR.22.8.983","article-title":"Atrial fibrillation as an independent risk factor for stroke: the Framingham Study","volume":"22","author":"Wolf","year":"1991","journal-title":"Stroke."},{"key":"B2","doi-asserted-by":"publisher","first-page":"973","DOI":"10.1212\/WNL.28.10.973","article-title":"Epidemiologic assessment of chronic atrial fibrillation and risk of stroke: the Framingham study","volume":"28","author":"Wolf","year":"1978","journal-title":"Neurology."},{"key":"B3","doi-asserted-by":"publisher","first-page":"359","DOI":"10.1016\/S0002-9343(02)01236-6","article-title":"A population-based study of the long-term risks associated with atrial fibrillation: 20-year follow-up of the Renfrew\/Paisley study","volume":"113","author":"Stewart","year":"2002","journal-title":"Am J Med."},{"key":"B4","doi-asserted-by":"publisher","first-page":"35","DOI":"10.1161\/01.STR.24.1.35","article-title":"Classification of subtype of acute ischemic stroke. Definitions for use in a multicenter clinical trial. TOAST. Trial of Org 10172 in Acute Stroke Treatment","volume":"24","author":"Adams HP","year":"1993","journal-title":"Stroke."},{"key":"B5","doi-asserted-by":"publisher","first-page":"224","DOI":"10.1161\/01.CIR.89.1.224","article-title":"Asymptomatic arrhythmias in patients with symptomatic paroxysmal atrial fibrillation and paroxysmal supraventricular tachycardia","volume":"89","author":"Page","year":"1994","journal-title":"Circulation."},{"key":"B6","doi-asserted-by":"publisher","first-page":"369","DOI":"10.1023\/A:1009823001707","article-title":"Clinical relevance of silent atrial fibrillation: prevalence, prognosis, quality of life, and management","volume":"4","author":"Savelieva","year":"2000","journal-title":"J Interv Card Electrophysiol."},{"key":"B7","doi-asserted-by":"publisher","first-page":"2467","DOI":"10.1056\/NEJMoa1311376","article-title":"Atrial fibrillation in patients with cryptogenic stroke","volume":"370","author":"Gladstone","year":"2014","journal-title":"N Engl J Med."},{"key":"B8","doi-asserted-by":"publisher","first-page":"2478","DOI":"10.1056\/NEJMoa1313600","article-title":"Cryptogenic stroke and underlying atrial fibrillation","volume":"370","author":"Sanna","year":"2014","journal-title":"N Engl J Med."},{"key":"B9","doi-asserted-by":"publisher","first-page":"e125","DOI":"10.1161\/CIR.0000000000000665","article-title":"2019 AHA\/ACC\/HRS Focused Update of the 2014 AHA\/ACC\/HRS Guideline for the Management of Patients With Atrial Fibrillation: A Report of the American College of Cardiology\/American Heart Association Task Force on Clinical Practice Guidelines and the Heart Rhythm Society in Collaboration With the Society of Thoracic Surgeons","volume":"140","author":"January","year":"2019","journal-title":"Circulation."},{"key":"B10","doi-asserted-by":"publisher","first-page":"857","DOI":"10.7326\/0003-4819-146-12-200706190-00007","article-title":"Meta-analysis: antithrombotic therapy to prevent stroke in patients who have nonvalvular atrial fibrillation","volume":"146","author":"Hart","year":"2007","journal-title":"Ann Intern Med."},{"key":"B11","doi-asserted-by":"publisher","first-page":"410","DOI":"10.1016\/S1474-4422(21)00106-X","article-title":"Monitoring for atrial fibrillation after stroke","volume":"20","author":"Wasserlauf","year":"2021","journal-title":"Lancet Neurol."},{"key":"B12","doi-asserted-by":"publisher","first-page":"895","DOI":"10.1161\/STROKEAHA.115.012004","article-title":"Atrial fibrillation and mechanisms of stroke: time for a new model","volume":"47","author":"Kamel","year":"2016","journal-title":"Stroke."},{"key":"B13","doi-asserted-by":"publisher","first-page":"861","DOI":"10.1016\/S0140-6736(19)31721-0","article-title":"An artificial intelligence-enabled ECG algorithm for the identification of patients with atrial fibrillation during sinus rhythm: a retrospective analysis of outcome prediction","volume":"394","author":"Attia","year":"2019","journal-title":"Lancet."},{"key":"B14","doi-asserted-by":"publisher","first-page":"688","DOI":"10.1002\/ana.20617","article-title":"An evidence-based causative classification system for acute ischemic stroke","volume":"58","author":"Ay","year":"2005","journal-title":"Ann Neurol."},{"key":"B15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90","article-title":"Deep residual learning for image recognition","author":"He","year":"","journal-title":"2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (IEEE)"},{"key":"B16","doi-asserted-by":"publisher","first-page":"867","DOI":"10.1161\/STROKEAHA.116.016414","article-title":"Embolic stroke of undetermined source: a systematic review and clinical update","volume":"48","author":"Hart","year":"2017","journal-title":"Stroke."},{"key":"B17","doi-asserted-by":"publisher","first-page":"2278","DOI":"10.1161\/STROKEAHA.116.013713","article-title":"Risk stratification for recurrence and mortality in embolic stroke of undetermined source","volume":"47","author":"Ntaios","year":"2016","journal-title":"Stroke."},{"key":"B18","doi-asserted-by":"publisher","first-page":"1444","DOI":"10.1056\/NEJMoa011258","article-title":"A comparison of warfarin and aspirin for the prevention of recurrent ischemic stroke","volume":"345","author":"Mohr","year":"2001","journal-title":"N Engl J Med."},{"key":"B19","doi-asserted-by":"publisher","first-page":"2191","DOI":"10.1056\/NEJMoa1802686","article-title":"Rivaroxaban for stroke prevention after embolic stroke of undetermined source","volume":"378","author":"Hart","year":"2018","journal-title":"N Engl J Med."},{"key":"B20","doi-asserted-by":"publisher","first-page":"2893","DOI":"10.1093\/eurheartj\/ehw210","article-title":"2016 ESC Guidelines for the management of atrial fibrillation developed in collaboration with EACTS","volume":"37","author":"Kirchhof","year":"2016","journal-title":"Eur Heart J."},{"key":"B21","doi-asserted-by":"publisher","first-page":"e344","DOI":"10.1161\/STR.0000000000000211","article-title":"Guidelines for the Early Management of Patients With Acute Ischemic Stroke: 2019 Update to the 2018 Guidelines for the Early Management of Acute Ischemic Stroke: A Guideline for Healthcare Professionals From the American Heart Association\/American Stroke Association","volume":"50","author":"Powers","year":"2019","journal-title":"Stroke."},{"key":"B22","doi-asserted-by":"publisher","first-page":"105998","DOI":"10.1016\/j.jstrokecerebrovasdis.2021.105998","article-title":"Artificial intelligence-enabled ECG to identify silent atrial fibrillation in embolic stroke of unknown source","volume":"30","author":"Rabinstein","year":"2021","journal-title":"J Stroke Cerebrovasc Dis."},{"key":"B23","doi-asserted-by":"publisher","first-page":"2169","DOI":"10.1001\/jama.2021.6470","article-title":"Effect of long-term continuous cardiac monitoring vs usual care on detection of atrial fibrillation in patients with stroke attributed to large- or small-vessel disease: the STROKE-AF randomized clinical trial","volume":"325","author":"Bernstein","year":"2021","journal-title":"JAMA."},{"key":"B24","doi-asserted-by":"publisher","first-page":"1287","DOI":"10.1161\/CIRCULATIONAHA.120.047829","article-title":"Deep neural networks can predict new-onset atrial fibrillation from the 12-lead ECG and help identify those at risk of atrial fibrillation-related stroke","volume":"143","author":"Raghunath","year":"2021","journal-title":"Circulation."},{"key":"B25","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1016\/j.ahj.2021.05.006","article-title":"Batch enrollment for an artificial intelligence-guided intervention to lower neurologic events in patients with undiagnosed atrial fibrillation: rationale and design of a digital clinical trial","volume":"239","author":"Yao","year":"2021","journal-title":"Am Heart J."},{"key":"B26","doi-asserted-by":"publisher","first-page":"1236","DOI":"10.1111\/pace.12688","article-title":"Role of outpatient cardiac rhythm monitoring in cryptogenic stroke: a systematic review and meta-analysis","volume":"38","author":"Afzal","year":"2015","journal-title":"Pacing Clin Electrophysiol."},{"key":"B27","doi-asserted-by":"publisher","first-page":"2244","DOI":"10.1161\/STROKEAHA.120.029340","article-title":"Cost-Effectiveness of Extended Electrocardiogram Monitoring for Atrial Fibrillation After Stroke: A Systematic Review","volume":"51","author":"Chew","year":"2020","journal-title":"Stroke."},{"key":"B28","doi-asserted-by":"publisher","first-page":"213","DOI":"10.3988\/jcn.2021.17.2.213","article-title":"Left atrial diameter and atrial ectopic burden in patients with embolic stroke of undetermined source: risk stratification of atrial fibrillation with insertable cardiac monitor analysis","volume":"17","author":"Lee","year":"2021","journal-title":"J Clin Neurol."},{"key":"B29","doi-asserted-by":"publisher","first-page":"830","DOI":"10.1016\/j.jbi.2013.06.010","article-title":"Defining and measuring completeness of electronic health records for secondary use","volume":"46","author":"Weiskopf","year":"2013","journal-title":"J Biomed Inform."},{"key":"B30","doi-asserted-by":"publisher","first-page":"2470","DOI":"10.1161\/CIRCULATIONAHA.113.002449","article-title":"Incident atrial fibrillation among Asians, Hispanics, blacks, and whites","volume":"128","author":"Dewland","year":"2013","journal-title":"Circulation."},{"key":"B31","doi-asserted-by":"publisher","first-page":"389","DOI":"10.1016\/0002-8703(83)90208-9","article-title":"Coronary heart disease and atrial fibrillation: The Framingham Study","volume":"106","author":"Kannel","year":"1983","journal-title":"Am Heart J."},{"key":"B32","doi-asserted-by":"publisher","first-page":"385","DOI":"10.1016\/j.jelectrocard.2007.03.008","article-title":"Errors in the computerized electrocardiogram interpretation of cardiac rhythm","volume":"40","author":"Shah","year":"2007","journal-title":"J Electrocardiol."}],"container-title":["Frontiers in Cardiovascular Medicine"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fcvm.2022.865852\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,4,8]],"date-time":"2022-04-08T02:35:58Z","timestamp":1649385358000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fcvm.2022.865852\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,4,8]]},"references-count":32,"alternative-id":["10.3389\/fcvm.2022.865852"],"URL":"https:\/\/doi.org\/10.3389\/fcvm.2022.865852","relation":{},"ISSN":["2297-055X"],"issn-type":[{"value":"2297-055X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,4,8]]},"article-number":"865852"}}