{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T00:29:49Z","timestamp":1790728189628,"version":"4.1.0"},"reference-count":35,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"8","license":[{"start":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T00:00:00Z","timestamp":1787616000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["www.ahajournals.org"],"crossmark-restriction":true},"short-container-title":["Circulation"],"published-print":{"date-parts":[[2026,8,25]]},"abstract":"<jats:sec>\n                    <jats:title>BACKGROUND:<\/jats:title>\n                    <jats:p>Screening for atrial fibrillation (AF) on the basis of AF risk may be more effective. We aimed to develop, externally validate, and prospectively test a machine learning prediction model using electronic health records (EHRs) to guide AF screening.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>METHODS:<\/jats:title>\n                    <jats:p>\n                      We developed and validated a random forest prediction model for new AF within 6 months, using age, sex, and 10 comorbidities (Future Innovations in Novel Detection of Atrial Fibrillation [FIND-AF] 2.0) in EHRs in the United Kingdom (n=2 081 139), Japan (n=7 795 244), Israel (n=2 166 795), Canada (n=627 919), and China (n=149 145). We conducted a prospective study where participants \u226530 years old without AF and with a CHA\n                      <jats:sub>2<\/jats:sub>\n                      DS\n                      <jats:sub>2<\/jats:sub>\n                      -VASc score \u22652 in men and \u22653 in women, stratified by FIND-AF 2.0 into high and low risk, undertook 4 ECG recordings per day for 3 weeks using a handheld ECG recorder, with a primary outcome of newly diagnosed AF. We estimated stroke risk associated with nonanticoagulated AF in patients with high FIND-AF 2.0 risk in the FinACAF (Finnish Anticoagulation in Atrial Fibrillation) registry of patients with AF (n=229 565).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>RESULTS:<\/jats:title>\n                    <jats:p>\n                      FIND-AF 2.0 was applicable to all EHRs and showed good to excellent prediction performance (United Kingdom: area under the receiver operating characteristic curve [AUROC], 0.819 [95% CI, 0.809\u20130.829]; Israel: AUROC, 0.835 [95% CI, 0.828\u20130.842]; Japan: AUROC, 0.751 [95% CI, 0.745\u20130.757]; Canada: AUROC, 0.747 [95% CI, 0.741\u20130.753]; China: AUROC, 0.753 [95% CI, 0.725\u20130.771]), with AUROC&gt;0.7 in men and women in all cohorts, and improved performance compared with CHA\n                      <jats:sub>2<\/jats:sub>\n                      DS\n                      <jats:sub>2<\/jats:sub>\n                      -VASc and C\n                      <jats:sub>2<\/jats:sub>\n                      HEST (coronary artery disease or chronic obstructive pulmonary disease [1 point each]; hypertension [1 point]; elderly [age \u226575 years, 2 points]; systolic HF [2 points]; thyroid disease [hyperthyroidism, 1 point]). Of 1923 participants from 15 sites in the prospective study (mean age, 70.2 [SD 9.4] years), with a mean of 74.8 (SD, 19.4) ECG recordings, AF was diagnosed in 5 of 902 (0.6%) with low FIND-AF 2.0 risk and 46 of 1021 (4.5%) with high FIND-AF 2.0 risk (odds ratio, 8.46 [95% CI, 3.35\u201321.40],\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      &lt;0.001). Median AF burden among high FIND-AF 2.0 risk\u2013detected cases was 33.4% (interquartile range, 5.1%\u201391.6%), and 96.1% initiated oral anticoagulants. In the FinACAF registry, the rate of ischemic stroke for patients with high FIND-AF 2.0 risk, AF, and no anticoagulants was 6.0 events per 100 patient-years.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>CONCLUSIONS:<\/jats:title>\n                    <jats:p>The EHR-based machine learning model, FIND-AF 2.0, identifies a high-risk subpopulation for AF diagnosis among patients at elevated risk of stroke and could enable scalable, EHR-driven, risk-guided AF screening.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1161\/circulationaha.126.079391","type":"journal-article","created":{"date-parts":[[2026,7,28]],"date-time":"2026-07-28T09:00:52Z","timestamp":1785229252000},"page":"707-717","update-policy":"https:\/\/doi.org\/10.1161\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":1,"title":["Risk-Guided Screening for Atrial Fibrillation Using Electronic Health Records"],"prefix":"10.1161","volume":"154","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9895-9356","authenticated-orcid":true,"given":"Ramesh","family":"Nadarajah","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianhua","family":"Wu","sequence":"additional","affiliation":[{"name":"Wolfson Institute of Population Health, Queen Mary, University of London, London, United Kingdom (J.W., C.G.)."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ali","family":"Wahab","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Catherine","family":"Reynolds","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-3859-7809","authenticated-orcid":true,"given":"Mohammad","family":"Haris","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9283-9895","authenticated-orcid":true,"given":"Tobin","family":"Joseph","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Keerthenan","family":"Raveendra","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8149-3449","authenticated-orcid":true,"given":"Ben","family":"Hurdus","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Khalid","family":"Kazi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sheena","family":"Bennett","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5563-8296","authenticated-orcid":true,"given":"Chris","family":"Hayward","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-6353-2725","authenticated-orcid":true,"given":"Ben","family":"Mercer","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2770-1099","authenticated-orcid":true,"given":"Jing","family":"Kang","sequence":"additional","affiliation":[{"name":"Oral Clinical Research Unit, Faculty of Dentistry Oral Craniofacial Sciences, King\u2019s College London, London, United Kingdom (J.K.)."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1163-2751","authenticated-orcid":true,"given":"Chenyi","family":"Gao","sequence":"additional","affiliation":[{"name":"Wolfson Institute of Population Health, Queen Mary, University of London, London, United Kingdom (J.W., C.G.)."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3627-5626","authenticated-orcid":true,"given":"Yoko M.","family":"Nakao","sequence":"additional","affiliation":[{"name":"Department of Pharmacoepidemiology, University of Kyoto, Kyoto, Japan (Y.M.N., K. 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