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Background: Brugada syndrome is a rare inherited arrhythmic syndrome with a coved type 1 ST-segment elevation on ECG and an increased risk of sudden death. Many studies have evaluated risk stratification performance based on ECG-derived parameters. However, since historical Brugada patient cohorts included mostly paper ECGs, most studies have been based on manual ECG parameter measurements. We hypothesized that it would be possible to run automated algorithm-based analysis of paper ECGs. We aimed: 1) to validate the digitization process for paper ECGs in Brugada patients; and 2) to quantify the acute class I antiarrhythmic drug effect on relevant ECG parameters in Brugada syndrome.Methods: A total of 176 patients (30% female, 43 ± 13 years old) with induced type 1 Brugada syndrome ECG were included in the study. All of the patients had paper ECGs before and during class I antiarrhythmic drug challenge. Twenty patients also had a digital ECG, in whom printouts were used to validate the digitization process. Paper ECGs were scanned and then digitized using ECGScan software, version 3.4.0 (AMPS, LLC, New York, NY, USA) to obtain FDA HL7 XML format ECGs. Measurements were automatically performed using the Bravo (AMPS, LLC, New York, NY, USA) and Glasgow algorithms.Results: ECG parameters obtained from digital and digitized ECGs were closely correlated (r = 0.96 ± 0.07, R2 = 0.93 ± 0.12). Class I antiarrhythmic drugs significantly increased the global QRS duration (from 113 ± 20 to 138 ± 23, p < 0.0001). On lead V2, class I antiarrhythmic drugs increased ST-segment elevation (from 110 ± 84 to 338 ± 227 μV, p < 0.0001), decreased the ST slope (from 14.9 ± 23.3 to -27.4 ± 28.5, p < 0.0001) and increased the TpTe interval (from 88 ± 18 to 104 ± 33, p < 0.0001).Conclusions: Automated algorithm-based measurements of depolarization and repolarization parameters from digitized paper ECGs are reliable and could quantify the acute effects of class 1 antiarrhythmic drug challenge in Brugada patients. Our results support using computerized automated algorithm-based analyses from digitized paper ECGs to establish risk stratification decision trees in Brugada syndrome. [ABSTRACT FROM AUTHOR]

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. We aimed to assess the predictive value of multi ECG parameters measured automatically in patients with Brugada syndrome. We performed a prospective, multicenter cohort study including Brugada patients with at least one available type 1 ECG (either spontaneously or drug-induced) between January 2005 and November 2021. Paper ECG were first digitized and then automatically analyzed using the Glasgow and Bravo algorithms. 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. ECGs from 301 Brugada patients (77% male, mean age at diagnosis 43 years, follow-up 7 ± 5.6 years) were analyzed. Brugada-related symptoms (cardiac syncope or major event) occurred in 23% of patients before diagnosis and 11% during follow-up (incidence: 1.57%/year). After multivariate Cox analysis, only 2 baseline ECG (without Ajmaline) parameters were significantly associated with major events: RR interval (HR = 1.01 [95%CI 1–1.01], P = 0.002) and QRS duration in lead V1 (HR = 1.04 [95%CI 1–1.07], P = 0.038). QRS prolongation in lead V1 > 113 ms (AUROC 0.69 [95%CI 0.58–0.8], Fig. 1) was associated with a 3-fold increased risk of major event [Fig. 2] (HR = 3.49 (95% CI [1.72–7.09], P = 0.001). Many previously described ECG parameter were not associated with major event in Brugada patients after multi-parameter evaluation. Sinus rate and QRS duration on lead V1 were independent risk factor. These results need to be validated on an external cohort. The predictive value of ECG parameters in Brugada syndrome should be assessed using automated multiparametric quantification. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: The efficacy of beta-blocker treatment in type 3 long QT syndrome (LQT3) remains debated., Objectives: The purpose of this study was to test the hypothesis that beta-blocker use is associated with cardiac events (CEs) in a French cohort of LQT3 patients., Methods: All patients with a likely pathogenic/pathogenic variant in the SCN5A gene (linked to LQT3) were included and followed-up. Documented ventricular tachycardia/ventricular fibrillation, torsades de pointes, aborted cardiac arrest, sudden death, and appropriate shocks were considered as severe cardiac events (SCEs). CEs also included syncope., Results: We included 147 patients from 54 families carrying 23 variants. Six of the patients developed symptoms before the age of 1 year and were analyzed separately. The 141 remaining patients (52.5% male; median age at diagnosis 24.0 years) were followed-up for a median of 11 years. The probabilities of a CE and an SCE from birth to the age of 40 were 20.5% and 9.9%, respectively. QTc prolongation (hazard ratio [HR] 1.12 [1.0-1.2]; P = .005]) and proband status (HR 4.07 [1.9-8.9]; P <.001) were independently associated with the occurrence of CEs. Proband status (HR 8.13 [1.7-38.8]; P = .009) was found to be independently associated with SCEs, whereas QTc prolongation (HR 1.11 [1.0-1.3]; P = .108) did not reach statistical significance. The cumulative probability of the age at first CE/SCE was not lower in patients treated with a beta-blocker., Conclusion: In agreement with the literature, proband status and lengthened QTc were associated with a higher risk of CEs. Our data do not show a protective effect of beta-blocker treatment., Competing Interests: Disclosures The authors have no conflicts to disclose., (Copyright © 2023 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.)