| アブストラクト | BACKGROUND: The increasing burden of atrial fibrillation (AF) emphasizes the need to identify high-risk individuals for enrolment in clinical trials of AF screening and primary prevention. We aimed to develop prediction models to identify individuals at high-risk of AF across prediction horizons from 6-months to 10-years. METHODS: We used secondary-care linked primary care electronic health record data from individuals aged >/=30 years without known AF in the UK Clinical Practice Research Datalink-GOLD dataset between January 2, 1998 and November 30, 2018; randomly divided into derivation (80%) and validation (20%) datasets. Models were derived using logistic regression from known AF risk factors for incident AF in prediction periods of 6 months, 1-year, 2-years, 5-years, and 10-years. Performance was evaluated using in the validation dataset with bootstrap validation with 200 samples, and compared against the CHA(2)DS(2)-VASc and C(2)HEST scores. RESULTS: Of 2,081,139 individuals in the cohort (1,664,911 in the development dataset, 416,228 in the validation dataset), the mean age was 49.9 (SD 15.4), 50.7% were women, and 86.7% were white. New cases of AF were 7,386 (0.4%) within 6 months, 15,349 (0.7%) in 1 year, 38,487 (1.8%) in 5 years, and 79,997 (3.8%) by 10 years. Valvular heart disease and heart failure were the strongest predictors, and association of hypertension with AF increased at longer prediction horizons. The optimal risk models incorporated age, sex, ethnicity, and 8 comorbidities. The models demonstrated good-to-excellent discrimination and strong calibration across prediction horizons (AUROC, 95%CI, calibration slope: 6-months, 0.803, 0.789-0.821, 0.952; 1-year, 0.807, 0.794-0.819, 0.962; 2-years, 0.815, 0.807-0.823, 0.973; 5-years, 0.807, 0.803-0.812, 1.000; 10-years 0.780, 0.777-0.784, 1.010), and superior to the CHA(2)DS(2)-VASc and C(2)HEST scores. The models are available as a web-based FIND-AF calculator. CONCLUSIONS: The FIND-AF models demonstrate high discrimination and calibration across short- and long-term prediction horizons in 2 million individuals. Their utility to inform trial enrolment and clinical decisions for AF screening and primary prevention requires further study. |
|---|
| ジャーナル名 | American heart journal |
|---|
| 投稿日 | 2024/3/9 |
|---|
| 投稿者 | Wu, Jianhua; Nadarajah, Ramesh; Nakao, Yoko M; Nakao, Kazuhiro; Arbel, Ronen; Haim, Moti; Zahger, Doron; Lip, Gregory Y H; Cowan, J Campbell; Gale, Chris P |
|---|
| 組織名 | Wolfson Institute of Population Health, Queen Mary, University of London, UK.;Leeds Institute of Data Analytics, University of Leeds, UK; Leeds Institute for;Cardiovascular and Metabolic Medicine, University of Leeds, UK; Department of;Cardiology, Leeds Teaching Hospitals NHS Trust, Leeds, UK. Electronic address:;r.nadarajah@leeds.ac.uk.;Pharmacoepidemiology, Graduate School of Medicine and Public Health, Kyoto;University, Kyoto, Japan.;Cardiovascular Medicine, National Cerebral and Cardiovascular Medicine, Suita,;Japan.;Community Medical Services Division, Clalit Health Services, Tel Aviv, Israel;;Maximizing Health Outcomes Research Lab, Sapir College, Sderot, Israel.;Department of Cardiology, Soroka University Medical Center, Beer Sheva, Israel;;Faculty of Health Sciences, Ben Gurion University of the Negev, Beer Sheva,;Israel.;Liverpool Centre for Cardiovascular Science at University of Liverpool, Liverpool;John Moores University and Liverpool Heart & Chest Hospital, Liverpool, UK;;Danish Center for Health Services Research, Department of Clinical Medicine,;Aalborg University, Aalborg, Denmark.;Department of Cardiology, Leeds Teaching Hospitals NHS Trust, Leeds, UK.;Leeds Institute for Cardiovascular and Metabolic Medicine, University of Leeds,;UK; Department of Cardiology, Leeds Teaching Hospitals NHS Trust, Leeds, UK;;Department of Pharmacoepidemiology, Graduate School of Medicine and Public;Health, Kyoto University, Kyoto, Japan. |
|---|
| Pubmed リンク | https://www.ncbi.nlm.nih.gov/pubmed/38458372/ |
|---|
