Automatized quantitative electrocardiography from digitized paper electrocardiograms: A new avenue for risk stratification in patients with Brugada syndrome.

Abstract

Background: Arrhythmic risk stratification is a major challenge in Brugada syndrome. Studies have evaluated risk stratification based on manually measured electrocardiogram (ECG) parameters at baseline and/or after drug challenge.

Aim: To assess the predictive value of multiple ECG parameters measured automatically from digitized paper ECGs.

Methods: During a prospective, multicentre cohort study that included patients with Brugada syndrome with type 1 ECG (spontaneously or drug-induced), paper ECGs were digitized and analysed. Major events were sudden cardiac death, aborted cardiac arrest and appropriate implantable cardioverter-defibrillator (ICD) therapy in the ventricular fibrillation (VF) zone. The predictive value of clinical and ECG parameters was assessed using univariable and multivariable Cox models.

Results: ECGs from 301 patients (74% male, mean age 43.1±13.3years, mean follow-up 7.1±5.6years) were analysed. Major events occurred in 6% of patients before diagnosis and 8% during follow-up. Two baseline ECG parameters were independently associated with major events: QRS prolongation in lead V1>113ms (hazard ratio [HR] 3.49, 95% confidence interval [CI] 1.72-7.09; P<0.001) and S duration on DI>33.5ms (HR 3.56, 95% CI 1.52-8.31; P<0.01). In drug-induced patients, changes in the Tpeak-Tend interval on V2 were associated with major events (HR 4.69, 95% CI 1.21-18.17; P=0.014).

Conclusion: Paper ECG datasets could be used for automatic quantitative ECG measurements. We confirmed the association of previously described parameters with events and identified useful new parameters. Multi-parametric ECG quantification may be used to assess risk in patients with Brugada syndrome.