Prediction of ventricular arrhythmias in patients with a spontaneous Brugada type 1 pattern: the key is in the electrocardiogram

There is currently no reliable tool to quantify the risks of ventricular fibrillation or sudden cardiac arrest (VF/SCA) in patients with spontaneous Brugada type 1 pattern (BrT1). Previous studies showed that electrocardiographic (ECG) markers of depolarization or repolarization disorders might indicate elevated risk. We aimed to design a VF/SCA risk prediction model based on ECG analyses for adult patients with spontaneous BrT1.

This retrospective multicentre international study analysed ECG data from 115 patients (mean age 45.1 ± 12.8 years, 105 males) with spontaneous BrT1. Of these, 45 patients had experienced VF/SCA and 70 patients did not experience VF/SCA. Among 10 ECG markers, a univariate analysis showed significant associations between VF/SCA and maximum corrected T_peak–T_end intervals ≥100 ms in precordial leads (LMaxT_pec) (P < 0.001), BrT1 in a peripheral lead (pT1) (P = 0.004), early repolarization in inferolateral leads (ER) (P < 0.001), and QRS duration ≥120 ms in lead V2 (P = 0.002). The Cox multivariate analysis revealed four predictors of VF/SCA: the LMaxT_pec [hazard ratio (HR) 8.3, 95% confidence interval (CI) 2.4–28.5; P < 0.001], LMaxT_pec + ER (HR 14.9, 95% CI 4.2–53.1; P < 0.001), LMaxT_pec + pT1 (HR 17.2, 95% CI 4.1–72; P < 0.001), and LMaxT_pec + pT1 + ER (HR 23.5, 95% CI 6–93; P < 0.001). Our multidimensional penalized spline model predicted the 1-year risk of VF/SCA, based on age and these markers.

LMaxT_pec and its association with pT1 and/or ER indicated elevated VF/SCA risk in adult patients with spontaneous BrT1. We successfully developed a simple risk prediction model based on age and these ECG markers.