Simple risk scoring using sinus rhythm electrocardiograms predicts the incidence of atrial fibrillation in the general population

Abstract

Abstract Atrial fibrillation (AF) is an arrhythmic disease. Prediction of AF development in healthy individuals is important before serious complications occur. We aimed to develop a risk prediction score for future AF using participants’ data, including electrocardiogram (ECG) measurements and information such as age and sex. We included 88,907 Japanese participants, aged 30–69 years, who were randomly assigned to derivation and validation cohorts in a ratio of 1:1. We performed multivariate logistic regression analysis and obtained the standardised beta coefficient of relevant factors and assigned scores to them. We created a score based on prognostic factors for AF to predict its occurrence after five years and applied it to validation cohorts to assess its reproducibility. The risk score ranged from 0 to 17, consisting of age, sex, PR prolongation, QT corrected for heart rate prolongation, left ventricular hypertrophy, premature atrial contraction, and left axis deviation. The area under the curve was 0.75 for the derivation cohort and 0.73 for the validation cohort. The incidence of new-onset AF reached over 2% at 10 points of the risk score in both cohorts. Thus, in this study, we showed the possibility of predicting new-onset AF using ECG findings and simple information.