Validation of multiparametric approaches for the prediction of sudden cardiac death in patients with Brugada syndrome and electrophysiological study

Abstract

Introduction and objectivesMultiparametric scores have been designed for better risk stratification in Brugada syndrome (BrS). We aimed to validate 3 multiparametric approaches (the Delise score, Sieira score and the Shanghai BrS Score) in a cohort with Brugada syndrome and electrophysiological study (EPS). MethodsWe included patients diagnosed with BrS and previous EPS between 1998 and 2019 in 23 hospitals. C-statistic analysis and Cox proportional hazard regression models were used. ResultsA total of 831 patients were included (mean age, 42.8±13.1; 623 [75%] men; 386 [46.5%] had a type 1 electrocardiogram (ECG) pattern, 677 [81.5%] were asymptomatic, and 319 [38.4%] had an implantable cardioverter-defibrillator). During a follow-up of 10.2±4.7 years, 47 (5.7%) experienced a cardiovascular event. In the global cohort, a type 1 ECG and syncope were predictive of arrhythmic events. All risk scores were significantly associated with events. The discriminatory abilities of the 3 scores were modest (particularly when these scores were evaluated in asymptomatic patients). Evaluation of the Delise and Sieira scores with different numbers of extra stimuli (1 or 2 vs 3) did not substantially improve the event prediction c-index. ConclusionsIn BrS, classic risk factors such as ECG pattern and previous syncope predict arrhythmic events. The predictive capabilities of the EPS are affected by the number of extra stimuli required to induce ventricular arrhythmias. Scores combining clinical risk factors with EPS help to identify the populations at highest risk, although their predictive abilities remain modest in the general BrS population and in asymptomatic patients.