Abstract
Aims
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.
Methods and results
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 Tpeak–Tend intervals ≥100 ms in precordial leads (LMaxTpec) (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 LMaxTpec [hazard ratio (HR) 8.3, 95% confidence interval (CI) 2.4–28.5; P < 0.001], LMaxTpec + ER (HR 14.9, 95% CI 4.2–53.1; P < 0.001), LMaxTpec + pT1 (HR 17.2, 95% CI 4.1–72; P < 0.001), and LMaxTpec + 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.
Conclusion
LMaxTpec 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.
Application of Business Risk Prediction Model: Based on the Logistic Regression Model
