{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,8]],"date-time":"2026-04-08T05:42:30Z","timestamp":1775626950800,"version":"3.50.1"},"reference-count":17,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2023,10,6]],"date-time":"2023-10-06T00:00:00Z","timestamp":1696550400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Noninvasive Electrocardiol"],"published-print":{"date-parts":[[2023,11]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>Access to long\u2010term ambulatory recording to detect atrial fibrillation (AF) is limited for economical and practical reasons. We aimed to determine whether 24\u2009h ECG (24hECG) data can predict AF detection on extended cardiac monitoring.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>We included all US patients from 2020, aged 17\u2013100\u2009years, who were monitored for 2\u201330\u2009days using the PocketECG device (MEDICALgorithmics), without AF \u226530\u2009s on the first day (<jats:italic>n<\/jats:italic>\u2009=\u200918,220, mean age 64.4\u2009years, 42.4% male). The population was randomly split into equal training and testing datasets. A Lasso model was used to predict AF episodes \u226530\u2009s occurring on days 2\u201330.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The final model included maximum heart rate, number of premature atrial complexes (PACs), fastest rate during PAC couplets and triplets, fastest rate during premature ventricular couplets and number of ventricular tachycardia runs \u22654 beats, and had good discrimination (ROC statistic 0.7497, 95% CI 0.7336\u20130.7659) in the testing dataset. Inclusion of age and sex did not improve discrimination. A model based only on age and sex had substantially poorer discrimination, ROC statistic 0.6542 (95% CI 0.6364\u20130.6720). The prevalence of observed AF in the testing dataset increased by quintile of predicted risk: 0.4% in Q1, 2.7% in Q2, 6.2% in Q3, 11.4% in Q4, and 15.9% in Q5. In Q1, the negative predictive value for AF was 99.6%.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>By using 24hECG data, long\u2010term monitoring for AF can safely be avoided in 20% of an unselected patient population whereas an overall risk of 9% in the remaining 80% of the population warrants repeated or extended monitoring.<\/jats:p><\/jats:sec>","DOI":"10.1111\/anec.13090","type":"journal-article","created":{"date-parts":[[2023,10,7]],"date-time":"2023-10-07T05:44:12Z","timestamp":1696657452000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Can 24\u2009h of ambulatory <scp>ECG<\/scp> be used to triage patients to extended monitoring?"],"prefix":"10.1111","volume":"28","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2249-8220","authenticated-orcid":false,"given":"Linda S.","family":"Johnson","sequence":"first","affiliation":[{"name":"Department of Clinical Sciences Lund University  Lund Sweden"},{"name":"MEDICALgorithmics  Warsaw Poland"},{"name":"Population Health Research Institute, McMaster University  Hamilton Ontario Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alexandra","family":"M\u00e5neheim","sequence":"additional","affiliation":[{"name":"Department of Clinical Sciences Lund University  Lund Sweden"},{"name":"Department of Clinical Physiology Sk\u00e5ne University Hospital  Malm\u00f6 Sweden"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Magdalena","family":"Slusarczyk","sequence":"additional","affiliation":[{"name":"MEDICALgorithmics  Warsaw Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Agnieszka","family":"Grotek","sequence":"additional","affiliation":[{"name":"MEDICALgorithmics  Warsaw Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Olga","family":"Witkowska","sequence":"additional","affiliation":[{"name":"MEDICALgorithmics  Warsaw Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Justinas","family":"Bacevicius","sequence":"additional","affiliation":[{"name":"Institute of Clinical Medicine, Faculty of Medicine Vilnius University  Vilnius Lithuania"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Leif","family":"S\u00f6rnmo","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering Lund University  Lund Sweden"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marek","family":"Dziubinski","sequence":"additional","affiliation":[{"name":"MEDICALgorithmics  Warsaw Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sanjeev","family":"Bhavnani","sequence":"additional","affiliation":[{"name":"Healthcare Innovation and Practice Transformation Laboratory, Scripps Clinic La Jolla\u2010Genesee Executive Plaza  San Diego California USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jeffrey S.","family":"Healey","sequence":"additional","affiliation":[{"name":"Population Health Research Institute, McMaster University  Hamilton Ontario Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gunnar","family":"Engstr\u00f6m","sequence":"additional","affiliation":[{"name":"Department of Clinical Sciences Lund University  Lund Sweden"},{"name":"Department of Clinical Physiology Sk\u00e5ne University Hospital  Malm\u00f6 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