Fiorenzo Gaita

Brugada syndrome (BrS) is an inherited electrical cardiac disorder that is associated with a higher risk of ventricular fibrillation (VF) and sudden cardiac death (SCD) in patients without structural heart disease. The diagnosis is based on the documentation of the typical pattern in the electrocardiogram (ECG) characterized by a J-point elevation of ≥2 mm, coved-type ST-segment elevation, and negative T wave in one or more right precordial leads, called type 1 Brugada ECG. Risk stratification is particularly difficult in asymptomatic cases. Patients who have experienced documented VF are generally recommended to receive an implantable cardioverter defibrillator to lower the likelihood of sudden death due to recurrent episodes. However, for asymptomatic individuals, the most appropriate course of action remains uncertain. Accurate risk prediction is critical to avoiding premature deaths and unnecessary treatments. Due to the challenges associated with experimental research on human cardiac tissue, alternative techniques such as computational modeling and deep learning-based artificial intelligence (AI) are becoming increasingly important. This study introduces a vision transformer (ViT) model that leverages 12-lead ECG images to predict potentially fatal arrhythmic events in BrS patients. This dataset includes a total of 278 ECGs, belonging to 210 patients which have been diagnosed with Brugada syndrome, and it is split into two classes: event and no event. The event class contains 94 ECGs of patients with documented ventricular tachycardia, ventricular fibrillation, or sudden cardiac death, while the no event class is composed of 184 ECGs used as the control group. At first, the ViT is trained on a balanced dataset, achieving satisfactory results (89% accuracy, 94% specificity, 84% sensitivity, and 89% F1-score). Then, the discarded no event ECGs are attached to additional 30 event ECGs, extracted by a 24 h recording of a singular individual, composing a new test set. Finally, the use of an optimized classification threshold improves the predictions on an unbalanced set of data (74% accuracy, 95% negative predictive value, and 90% sensitivity), suggesting that the ECG signal can reveal key information for the risk stratification of patients with Brugada syndrome.

Brugada syndrome mainly affects young subjects with structurally normal heart and can cause x syncope or sudden death due to ventricular arrhythmias, even as the first manifestation, in approximately 5–10% of cases. To date, two questions remain open: how to recognize subjects who will experience arrhythmic events and how to treat them. The guidelines suggest treating subjects with a previous history of cardiac arrest or arrhythmogenic syncope, while they are unconclusive about the management of asymptomatic patients, who represent ∼90% of Brugada patients. We recently demonstrated that in asymptomatic patients, the presence of spontaneous Brugada type 1 electrocardiogram (ECG) pattern and inducibility of ventricular arrhythmias at electrophysiological study allows us to identify a group of patients at greater risk who deserve treatment. Regarding treatment, there are three options: implantable cardioverter defibrillator, drugs, and epicardial transcatheter ablation. Recent studies have shown that the latter is effective and free from serious side effects, thus opening a new scenario in the treatment of Brugada patients at risk. Subjects who present drug-induced-only type 1 Brugada ECG pattern, in whom a spontaneous type 1 pattern has been ruled out with repeated ECGs and 12-lead 24-h Holter monitoring, represent a very low-risk group, provided they adhere to behavioural recommendations and undergo regular follow-up.

Based on the study Bergonti et al.¹² and other recent publications^7,14,15 the flow chart summarizes a possible role for an ILR and EPS in the risk stratification of Brugada patients and a proposal for different therapeutic management, which also considers possible alternatives to ICD implantation. EPS+, induction of sustained ventricular tacchycardia or ventricular fibrillation at electrophysiological study; EPS–, electrophysiological study without arrhythmia induction; ICD, implantable cardioverter defibrillator; ILR, implantable loop recorder.

BACKGROUND: Brugada syndrome poses significant challenges in terms of risk stratification and management, particularly for asymptomatic patients who comprise the majority of individuals exhibiting Brugada ECG pattern (BrECG). The aim of this study was to evaluate the long-term prognosis of a large cohort of asymptomatic patients with BrECG. METHODS: Asymptomatic patients with BrECG (1149) were consecutively collected from 2 Italian centers and followed-up at least annually for 2 to 22 years. For the 539 asymptomatic patients (men, 433 [80%]; mean age, 46±13 years) with spontaneous type 1 documented on baseline ECG (87%) or 12-lead 24-hour Holter monitoring (13%), an electrophysiologic study (EPS) was proposed; for the 610 patients with drug-induced–only type 1 (men, 420 [69%]; mean age, 44±14 years), multiple ECGs and 12-lead Holter were advised in order to detect the occurrence of a spontaneous type-1 BrECG. Arrhythmic events were defined as sudden death or documented ventricular fibrillation or tachycardia. RESULTS: Median follow-up was 6 (4–9) years. Seventeen (1.5%) arrhythmic events occurred in the overall asymptomatic population (corresponding to an event-rate of 0.2% per year), including 16 of 539 (0.4% per year) in patients with spontaneous type-1 BrECG and 1 of 610 in those with drug-induced type-1 BrECG (0.03% per year; P P =0.025). Among 200 patients who declined EPS, 5 events (0.4% per year) occurred. There was 1 device-related death. CONCLUSIONS: The entire population of asymptomatic patients with BrECG exhibits a relatively low event rate per year, which is important in view of the long life expectancy of these young patients. The presence of spontaneous type-1 BrECG associated with positive EPS identifies a subgroup at higher risk. Asymptomatic patients with drug-induced–only BrECG have a minimal arrhythmic risk, but ongoing follow-up with 12-lead Holter monitoring is recommended to detect the appearance of spontaneous type-1 BrECG pattern.