Novel Risk Prediction Model to Determine Adverse Heart Failure Outcomes in Arrhythmogenic Right Ventricular Cardiomyopathy

Abstract

Background Patients with arrhythmogenic right ventricular cardiomyopathy are at risk for life‐threatening ventricular tachyarrhythmias, but progressive heart failure (HF) may occur in later stages of disease. This study aimed to characterize potential risk predictors and develop a model for individualized assessment of adverse HF outcomes in arrhythmogenic right ventricular cardiomyopathy. Methods and Results Longitudinal and observational cohorts with 290 patients with arrhythmogenic right ventricular cardiomyopathy from the Fuwai Hospital in Beijing, China, and 99 patients from the University Heart Center in Zurich, Switzerland, with follow‐up data were studied. The primary end point of the study was heart transplantation or death attributable to HF. The model was developed by Cox regression analysis for predicting risk and was internally validated. During 4.92±3.03 years of follow‐up, 48 patients reached the primary end point. The determinants of the risk prediction model were left ventricular ejection fraction, serum creatinine levels, moderate‐to‐severe tricuspid regurgitation, and atrial fibrillation. Implantable cardioverter‐defibrillators did not reduce the occurrence of adverse HF outcomes. Conclusions A novel risk prediction model for arrhythmogenic right ventricular cardiomyopathy has been developed using 2 large and well‐established cohorts, incorporating common clinical parameters such as left ventricular ejection fraction, serum creatinine levels, tricuspid regurgitation, and atrial fibrillation, which can identify patients who are at risk for terminal HF events, and may guide physicians to assess individualized HF risk and to optimize management strategies.