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.
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.
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.
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.