Vollständiger Abstract
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BACKGROUND: 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. METHODS: 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 ≥30 years old without AF and with a CHA 2 DS 2 -VASc score ≥2 in men and ≥3 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). RESULTS: 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, 0.809–0.829]; Israel: AUROC, 0.835 [95% CI, 0.828–0.842]; Japan: AUROC, 0.751 [95% CI, 0.745–0.757]; Canada: AUROC, 0.747 [95% CI, 0.741–0.753]; China: AUROC, 0.753 [95% CI, 0.725–0.771]), with AUROC>0.7 in men and women in all cohorts, and improved performance compared with CHA 2 DS 2 -VASc and C 2 HEST (coronary artery disease or chronic obstructive pulmonary disease [1 point each]; hypertension [1 point]; elderly [age ≥75 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, 3.35–21.40], P
Bibliografischer Nachweis
Publikationsdaten
- Autor:innen
- Ramesh Nadarajah, Jianhua Wu, Ali Wahab, Catherine Reynolds, Mohammad Haris, Tobin Joseph, Keerthenan Raveendra, Ben Hurdus, Khalid Kazi, Sheena Bennett, Chris Hayward, Ben Mercer, Jing Kang, Chenyi Gao, Yoko M. Nakao, Koji Kawakami, Carlin Chang, Abraham Wai, Jiandong Zhou, Gary Tse, Talish Razi Benita, Lior Rokach, Ronen Arbel, Moti Haim, Doron Zahger, Dina Labib, Jacqueline Flewitt, James A. White, Konsta Teppo, Mika Lehto, Ville Langén, Aleksi K. Winstén, K.E. Juhani Airaksinen, Jari Haukka, Olli Halminen, Jukka Putaala, Juha Hartikainen, Miika Linna, Ben Freedman, Emma Svennberg
- Quelle
- Circulation
- Publikation
- 2026-01-01
- Band / Ausgabe
- Nicht angegeben
- Seiten
- Nicht angegeben
- ISSN / ISBN
- 0009-7322, 1524-4539
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Zitierfähiger Nachweis
Ramesh Nadarajah, Jianhua Wu, Ali Wahab, Catherine Reynolds, Mohammad Haris, Tobin Joseph, Keerthenan Raveendra, Ben Hurdus, Khalid Kazi, Sheena Bennett, Chris Hayward, Ben Mercer, Jing Kang, Chenyi Gao, Yoko M. Nakao, Koji Kawakami, Carlin Chang, Abraham Wai, Jiandong Zhou, Gary Tse, Talish Razi Benita, Lior Rokach, Ronen Arbel, Moti Haim, Doron Zahger, Dina Labib, Jacqueline Flewitt, James A. White, Konsta Teppo, Mika Lehto, Ville Langén, Aleksi K. Winstén, K.E. Juhani Airaksinen, Jari Haukka, Olli Halminen, Jukka Putaala, Juha Hartikainen, Miika Linna, Ben Freedman, Emma Svennberg (2026). Risk-Guided Screening for Atrial Fibrillation Using Electronic Health Records. Circulation. https://doi.org/10.1161/circulationaha.126.079391
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