{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T13:52:12Z","timestamp":1772805132989,"version":"3.50.1"},"reference-count":35,"publisher":"Wiley","issue":"10","license":[{"start":{"date-parts":[[2020,8,30]],"date-time":"2020-08-30T00:00:00Z","timestamp":1598745600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Ann Clin Transl Neurol"],"published-print":{"date-parts":[[2020,10]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Objective<\/jats:title><jats:p>Identification of ischemic stroke patients at high risk for paroxysmal atrial fibrillation (pAF) during 72\u00a0hours Holter ECG might be useful to individualize the allocation of prolonged ECG monitoring times, currently not routinely applied in clinical practice.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>In a prospective multicenter study, the first analysable hour of raw ECG data from prolonged 72\u00a0hours Holter ECG monitoring in 1031 patients with acute ischemic stroke\/TIA presenting in sinus rhythm was classified by an automated software (AA) into \u201cno risk of AF\u201d or \u201crisk of AF\u201d and compared to clinical variables to predict AF during 72\u00a0hours Holter\u2010ECG.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>pAF was diagnosed in 54 patients (5.2%; mean age: 78\u00a0years; female 56%) and was more frequently detected after 72\u00a0hours in patients classified by AA as \u201crisk of AF\u201d (n\u00a0=\u00a021, 17.8%) compared to \u201cno risk of AF\u201d (n\u00a0=\u00a033, 3.6%). AA\u2010based risk stratification as \u201crisk of AF\u201d remained in the prediction model for pAF detection during 72\u00a0hours Holter ECG (OR3.814, 95% CI 2.024\u20107.816, <jats:italic>P<\/jats:italic>\u00a0&lt;\u00a00.001), in addition to age (OR1.052, 95% CI 1.021\u20101.084, <jats:italic>P<\/jats:italic>\u00a0=\u00a00.001), NIHSS (OR 1.087, 95% CI 1.023\u20101.154, <jats:italic>P<\/jats:italic>\u00a0=\u00a00.007) and prior treatment with thrombolysis (OR2.639, 95% CI 1.313\u20105.306, <jats:italic>P<\/jats:italic>\u00a0=\u00a00.006). Similarly, risk stratification by AA significantly increased the area under the receiver operating characteristic curve (AUC) for prediction of pAF detection compared to a purely clinical risk score (AS5F alone: AUC 0.751; 95% CI 0.724\u20100.778; AUC for the combination: 0.789, 95% CI 0.763\u20100.814; difference between the AUC <jats:italic>P<\/jats:italic>\u00a0=\u00a00.022).<\/jats:p><\/jats:sec><jats:sec><jats:title>Interpretation<\/jats:title><jats:p>Automated software\u2010based ECG risk stratification selects patients with high risk of AF during 72\u00a0hours Holter ECG and adds predictive value to common clinical risk factors for AF prediction.<\/jats:p><\/jats:sec>","DOI":"10.1002\/acn3.51157","type":"journal-article","created":{"date-parts":[[2020,8,30]],"date-time":"2020-08-30T10:54:33Z","timestamp":1598784873000},"page":"1779-1787","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Software\u2010based 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