ST-segment slope change in V1 predict major events in Brugada syndrome

Arrhythmic risk stratification remains a major challenge in asymptomatic Brugada patients. Many studies have evaluated risk stratification performance based on a single or a few ECG-derived parameters measured manually on baseline and/or after drug challenge ECGs. We aimed to assess the predictive value of ECG changes induced by pharmacological challenge in patients with drug induced type 1 Brugada pattern. We performed a prospective, multicenter cohort study including Brugada patients with one available drug-induced type 1 ECG and one baseline ECG between January 2005 and November 2021. Paper ECG were first digitized and then automatically analyzed using the Glasgow and Bravo algorithms. A non-normalized ECG change (ΔECG) was calculated between the parameters of the drug-induced and baseline ECG. Clinical data and Brugada related events at diagnosis and during follow-up were collected. Sudden cardiac death, aborted cardiac arrest and appropriate ICD therapy in the VF zone were considered as major events. The predictive value of clinical and ECG parameters for symptomatic status was assessed using uni- and multivariate Cox models. Off- and on-drug ECGs from 164 Brugada patients (72% male, mean age at diagnosis 43 years, follow-up 5.9 ± 4.9 years) were analyzed. Brugada-related symptoms (cardiac syncope or major event) occurred in 26% of patients before diagnosis and 6% during follow-up (incidence: 1.57%/year). After multivariate Cox analysis, 2 ΔECG parameters were also significantly associated with major events: ΔTpeak-Tend V1 (HR = 0.99, CI 95% [0.97–1], P = 0.017) and ΔST-segment Slope V1 (HR = 1, CI 95% [1–1.01], P = 0.014). ST-segment slope change in V1 > 219.5 μV/ms (AUROC 0.75 (95% CI [0.76–0.8]), Fig. 1) was associated with an increased risk of major event [Fig. 2] (HR = 11.59 (CI 95% [2.45–54.86]), P = 0.002). The magnitude of drug-induced ECG changes is associated with major event in Brugada patients. These results need to be validated on an external cohort but our results support using automated multiparametric ECG quantification for risk stratification in Brugada patients.