%0 Journal Article %A Ancor Sanz-García %A Alberto Cecconi %A Alberto Vera %A Juan Miguel Camarasaltas %A Fernando Alfonso %A Guillermo Jose Ortega %A Jesus Jimenez-Borreguero %T Electrocardiographic biomarkers to predict atrial fibrillation in sinus rhythm electrocardiograms %D 2021 %R 10.1136/heartjnl-2021-319120 %J Heart %P heartjnl-2021-319120 %X Objective Early prediction of atrial fibrillation (AF) development would improve patient outcomes. We propose a simple and cheap ECG based score to predict AF development.Methods A cohort of 16 316 patients was analysed. ECG measures provided by the computer-assisted ECG software were used to identify patients. A first group included patients in sinus rhythm who showed an ECG with AF at any time later (n=505). A second group included patients with all their ECGs in sinus rhythm (n=15 811). By using a training set (75% of the cohort) the initial sinus rhythm ECGs of both groups were analysed and a predictive risk score based on a multivariate logistic model was constructed.Results A multivariate regression model was constructed with 32 variables showing a predictive value characterised by an area under the curve (AUC) of 0.776 (95% CI: 0.738 to 0.814). The subsequent risk score included the following variables: age, duration of P-wave in aVF, V4 and V5; duration of T-wave in V3, mean QT interval adjusted for heart rate, transverse P-wave clockwise rotation, transverse P-wave terminal angle and transverse QRS complex terminal vector magnitude. Risk score values ranged from 0 (no risk) to 5 (high risk). The predictive validity of the score reached an AUC of 0.764 (95% CI: 0.722 to 0.806) with a global specificity of 61% and a sensitivity of 55%.Conclusions The automatic assessment of ECG biomarkers from ECGs in sinus rhythm is able to predict the risk for AF providing a low-cost screening strategy for early detection of this pathology.No data are available. %U https://heart.bmj.com/content/heartjnl/early/2021/06/03/heartjnl-2021-319120.full.pdf