A Novel Electrocardiographic Prediction Model For Diagnosing Concealed Brugada Syndrome: Results From A Clinical Trial Of Ajmaline Provocation In Healthy Subjects

BackgroundClinical, electrocardiographic, and genomic factors have been associated with the drug-induced type 1 Brugada pattern (DI-T1BP), in response to sodium channel blocker provocation (SCBP). However, prior analyses have been concerned with prediction of the DI-T1BP rather than the validity of the diagnosis of concealed Brugada syndrome (BrS). We sought to analyse and compare the ECG response to SCBP with ajmaline in a cohort of healthy controls (HC) and a definite BrS group (Def-BrS) to develop a diagnostic score. MethodsHealthy controls (HC) were systematically recruited as part of a clinical trial. Following comprehensive cardiovascular screening, eligible subjects underwent SCBP with ajmaline. We identified a Def-BrS cohort, defined as a DI-T1BP and a Shanghai Score (SS) >3.5, from consecutive patients with suspected BrS undergoing SCBP with ajmaline using the identical protocol. Def-BrS and HC were divided equally into discovery and validation cohorts. Digital ECG acquisition facilitated automated measurement of ECG parameters. A multivariable analysis compared ECG parameters between the HC and Def-BrS cohorts. A logistic regression analysis identified ECG characteristics that accurately predicted the diagnosis of Def-BrS. This model was then assessed in the validation cohort. ResultsTwo-hundred-and-forty-eight volunteers completed an online questionnaire, 103 accepted an invitation to undergo further screening and 100 were recruited into the HC group. Three HCs developed a DI-T1BP. From 1241 patients undergoing SCBP, 166 were Def-BrS. There were no demographic differences between the HC discovery and validation groups or between the Def-BrS discovery and validation groups. Following multivariable logistic regression analysis, QRS duration, mean anterior lead ST segment amplitude at baseline, maximum change in QRS duration, anterior ST segment amplitude and QRS area after SCBP, were independently associated with Def-BrS. The combined model was an excellent discriminator for Def-BrS, with an area under the curve of 0.95 [95% confidence interval (CI) = 0.912 - 0.989], P<0.001 in the discovery groups and 0.97 [95% CI = 0.948 - 0.998], P<0.001 in the validation groups. ConclusionThe yield of the DI-T1BP in HCs is 3%. However, there are distinct ECG parameters at baseline and in response to SCBP that favour a definite diagnosis of BrS. These observations permit the quantifiable refinement of the ECG diagnosis of concealed BrS, avoiding the pitfalls of relying upon the DI-T1BP alone.