Abstract

AIMS: Arrhythmogenic right ventricular cardiomyopathy (ARVC) is a genetically determined heart muscle disorder associated with an increased risk of life-threatening arrhythmias in some patients. Risk stratification remains challenging. Therefore, we sought a non-invasive, easily applicable risk score to predict sustained ventricular arrhythmias in these patients. METHODS: Cohort of Patients who fulfilled the 2010 ARVC task force criteria were consecutively recruited. Detailed clinical data were collected at baseline and during follow up. The clinical endpoint was a composite of recurrent sustained ventricular arrhythmias and hospitalization due to ventricular arrhythmias. Multivariable logistic regression was used to develop models to predict the arrhythmic risk. A cohort including patients from other registries in UK, Canada and Switzerland was used as a validation population. RESULTS: One hundred and thirty-five patients were included of whom 35 patients (31.9%) reached the endpoint. A model consisting of filtered QRS duration on signal-averaged ECG, non-sustained VT (NSVT) on 24 h-ECG, and absence of negative T waves in lead aVR on 12‑lead surface ECG was able to predict arrhythmic events with a sensitivity of 81.8%, specificity of 84.0% and a negative predictive value of 95.5% at the first presentation of the disease. This risk score was validated in international ARVC registry patients. CONCLUSION: A risk score consisting of a filtered QRS duration ≥117 ms, presence of NSVT on 24 h-ECG and absence of negative T waves in lead aVR was able to predict arrhythmic events at first presentation of the disease.