Development of a risk model for predicting QTc interval prolongation in patients using QTc-prolonging drugs.

Abstract

Background Numerous drugs prolong the QTc interval on the ECG and potentially increase the risk of cardiac arrhythmia. This risk is clinically relevant in patients with additional risk factors. Objective The objective was to develop and validate a risk model to predict QTc interval prolongation of eligible ECGs. Setting Spaarne Gasthuis (Haarlem/Hoofddorp, The Netherlands). Method A dataset was created from ECGs recorded in patients using one or more QTc prolonging drugs, in the period January 2013 and October 2016.In the development set, independent risk factors for QTc interval prolongation were determined using binary logistic regression. Risk scores were assigned based on the beta coefficient. In the risk-score validation set, the area under the ROC-curve, sensitivity and specificity were calculated. Main outcome measure QTc interval prolongation, defined as a QTc interval > 500ms. Results In the development set 12,949 ECGs were included and in the risk-score validation set 6391 ECGs. The proportion of ECGs with a prolonged QTc interval in patients with no risk factors in the risk-score validation set was 2.7%, while in patients with a high risk score the proportion was 26.1%. The area under the ROC curve was 0.71 (95% CI 0.68-0.73). The sensitivity and specificity were 0.81 and 0.48, respectively. Conclusion A risk model was developed and validated for the prediction of QTc interval prolongation. This risk model can be implemented in a clinical decision support system, supporting the management of the risks involved with QTc interval prolonging drugs.