PO-03-198 A NOVEL ELECTROCARDIOGRAPHIC MODEL FOR DEFINITE DRUG INDUCED BRUGADA SYNDROME.

Abstract

Clinical, electrocardiographic, and genomic factors associated with the development of the drug induced type 1 Brugada pattern (DI-T1BP), in response to sodium channel blocker provocation (SCBP) have been investigated. These prior analyses have mostly been concerned with the prediction of the DI-T1BP rather than the strength of the diagnosis of Brugada syndrome (BrS). To analyse and compare the ECG response to SCBP with Ajmaline in a cohort of healthy subjects (Healthy Controls) and clinical patients with a DI-T1BP and a Shanghai Score (SS) ≥3.5 (Definite-BrS group). From an existing clinical cohort of consecutive patients investigated at our centre between 2010 - 2022, we identified those with a DI-T1BP and a SS ≥3.5. Respondents to a national advertisement for healthy volunteers completed an online medical questionnaire. Those fulfilling inclusion criteria were invited to undergo further evaluation with eligible subjects undergoing a diagnostic ajmaline challenge. Digital ECG acquisition facilitated the development of automated measurements. A univariable analysis following by a multivariable analysis were undertaken to compare ECG characteristics between the two groups. A logistic regression analysis was performed to identify ECG characteristics that accurately associated with the definite drug induced BrS patient group. Two-hundred-and-forty-eight volunteers completed an online questionnaire, 103 accepted an invitation to undergo further screening and 100 were recruited into the healthy control (HC) group including three with a DI-T1BP. From a cohort of 1241 consecutive patients undergoing ajmaline provocation, 372 had a DI-T1BP and 166 had a DI-T1BP and SS ≥3.5. Of the ECG characteristics investigated, ajmaline induced changes (delta) in precordial QRS area (mv/ms), Anterior STJ point amplitude (μV) and S wave duration in lead II (ms), were independent predictors of definite BrS, Table 1.0. A model incorporating these 3 ECG characteristics was an outstanding discriminator with an area under the curve of 0.937 [95% confidence interval 0.907 – 0.966], P<0.01, Figure 1. This novel predictive model demonstrates excellent discrimination between patients with definite BrS and healthy controls. Further refinement of this model in clinical patients with DI-T1BP and SS <3.5 will identify additional clinical characteristics that can be incorporated into a clinical-ECG diagnostic model.