Development and Validation of 3-Year Atrial Fibrillation Prediction Models Using Electronic Health Record With or Without Standardized Electrocardiogram Diagnosis and a Performance Comparison Among Models.

ABSTRACT: Background Improved prediction of atrial fibrillation (AF) may allow for earlier interventions for stroke prevention, as well as mortality and morbidity from other AF-related complications. We developed a clinically feasible and accurate AF prediction model using electronic health records and computerized ECG interpretation. Methods and Results A total of 671 318 patients were screened from 3 tertiary hospitals. After careful exclusion of cases with missing values and a prior AF diagnosis, AF prediction models were developed from the derivation cohort of 25 584 patients without AF at baseline. In the internal/external validation cohort of 117 523 patients, the model using 6 clinical features and 5 ECG diagnoses showed the highest performance for 3-year new-onset AF prediction (C-statistic,

SUBMITTER: Yum Y 

PROVIDER: S-EPMC9238645 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature