Contemporary Perspectives on J-Wave Syndromes: An Expert Consensus Statement

J-wave syndromes (JWS)-comprising Brugada syndrome (BrS) and early repolarization syndrome (ERS)-are important causes of malignant ventricular arrhythmias and sudden cardiac death in patients whose hearts appear structurally normal. Since the 2016 consensus, advances in genetics, pathophysiology, and therapy have redefined both understanding and management. BrS, once viewed as a purely electrical disorder, is now recognized along a microstructural-electrical continuum, with sodium-channel dysfunction and subtle epicardial fibrosis of the right ventricular outflow tract as key contributors. Likewise, ERS-historically considered benign-carries significant risk when inferolateral J-waves coexist with arrhythmic events. Genetically, SCN5A remains the sole gene with definitive disease association, while polygenic susceptibility materially modulates risk, underscoring complex inheritance. Risk stratification remains challenging: patients with prior cardiac arrest or arrhythmic syncope are highest risk, whereas asymptomatic individuals warrant multiparametric assessment integrating clinical features, ECG markers, electrophysiologic studies, and genetics. For decades, treatment centered on implantable cardioverter-defibrillators and quinidine, both limited by availability, tolerance, and device complications. More recently, epicardial substrate ablation has emerged as a transformative therapy, with large registries and randomized trials demonstrating durable suppression of ventricular fibrillation and acceptable safety. This APHRS-organized international consensus updates and extends the 2016 Expert Consensus and the 2022 ESC Guidelines, providing contemporary diagnostic frameworks, pragmatic risk-stratification tools, and treatment algorithms for BrS and ERS. It emphasizes JWS as a microstructural-electrical disease spectrum and elevates substrate ablation as a major therapeutic advance, while outlining priorities for genetics, risk-stratification and treatment algorithms.