Beyond the type 1 pattern: comprehensive risk stratification in Brugada Syndrome

Brugada Syndrome (BrS) is an inherited cardiac ion channelopathy associated with an elevated risk of sudden cardiacdeath, particularly due to ventricular arrhythmias in structurally normal hearts. Affecting approximately 1 in 2,000 individ-uals, BrS is most prevalent among middle-aged males of Asian descent. Although diagnosis is based on the presence of aType 1 electrocardiographic (ECG) pattern, either spontaneous or induced, accurately stratifying risk in asymptomatic andborderline patients remains a major clinical challenge. This review explores current and emerging approaches to BrS riskstratification, focusing on electrocardiographic, electrophysiological, imaging, and computational markers. Non-invasiveECG indicators such as the β-angle, fragmented QRS, S wave in lead I, early repolarisation, aVR sign, and transmural dis-persion of repolarisation have demonstrated predictive value for arrhythmic events. Adjunctive tools like signal-averagedECG, Holter monitoring, and exercise stress testing enhance diagnostic yield by capturing dynamic electrophysiologicalchanges. In parallel, imaging modalities, particularly speckle-tracking echocardiography and cardiac magnetic resonancehave revealed subclinical structural abnormalities in the right ventricular outflow tract and atria, challenging the paradigmof BrS as a purely electrical disorder. Invasive electrophysiological studies and substrate mapping have further clarifiedthe anatomical basis of arrhythmogenesis, while risk scoring systems (e.g., Sieira, BRUGADA-RISK, PAT) and machinelearning models offer new avenues for personalised risk assessment. Together, these advances underscore the importanceof an integrated, multimodal approach to BrS risk stratification. Optimising these strategies is essential to guide implant-able cardioverter-defibrillator decisions and improve outcomes in patients vulnerable to life-threatening arrhythmias.

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