Ventricular Arrhythmia Prediction Model in ARVC
- The authors of this article pooled data from five databases of patients with arrhythmogenic right ventricular cardiomyopathy (ARVC).
- They identified seven predictors of incident ventricular arrhythmia or sudden cardiac death in ARVC patients: age at diagnosis, sex, cardiac syncope in the prior 6 months, nonsustained VT, number of premature ventricular complexes in 24 hours, number of leads with T-wave inversion, and RVEF.
- The ARVC risk score is available at https://arvcrisk.com.
Can a model be developed to predict incident ventricular arrhythmias/sudden cardiac death (VAs/SCD) in patients with arrhythmogenic right ventricular cardiomyopathy (ARVC)?
Patients with a definite diagnosis and no history of sustained VAs/SCD at baseline were pooled from five registries in North America and Europe. A prediction model estimating annual VA risk was developed using Cox regression. Eight potential predictors were prespecified: age, sex, cardiac syncope in the prior 6 months, nonsustained ventricular tachycardia (VT), number of premature ventricular complexes in 24 hours, number of leads with T-wave inversion, and RV and left ventricular ejection fractions (LVEFs).
There were 528 patients (45% male) with mean age of 38 years. Over average follow-up of 4.8 years, 146 (28%) experienced sustained VA, defined as SCD, aborted SCD, sustained VT, or appropriate implantable cardioverter-defibrillator (ICD) therapy. From among the eight prespecified potential predictors, only LVEF was not retained in the final model. The model accurately distinguished patients with and without events, with an optimism-corrected C-index of 0.77 (95% confidence interval [CI], 0.73-0.81) and minimal over-optimism (calibration slope of 0.93; (95% CI, 0.92-0.95). By decision curve analysis, the clinical benefit of the model was superior to a current consensus-based ICD placement algorithm with a 20.3% reduction of ICD placements with the same proportion of protected patients (p < 0.001).
Using the largest cohort of patients with ARVC and no prior VA, a prediction model using readily available clinical parameters was devised to estimate VA risk and guide decisions regarding primary prevention ICDs.
It has been accepted that most ARVC patients with a prior history of sustained VA or sudden cardiac arrest benefit from ICDs. Prior attempts to develop predictors of appropriate ICD therapy for the primary prevention population with ARVC have been hampered by the relatively small cohorts studied, which failed to provide statistical power to assess the independent predictive value of potentially correlated risk factors. The authors of this pooled analysis of five different registries (Johns Hopkins, Dutch, Nordic, Swiss, and Canadian) identified seven predictors of VT/VF/SCD: age at diagnosis, sex, cardiac syncope in the prior 6 months, nonsustained VT, number of premature ventricular complexes in 24 hours, number of leads with T-wave inversion, and RVEFs. This offers clinicians an easy to use and more discriminating risk stratification tool than prior expert consensus. The tool is available at https://arvcrisk.com. Of note, this article serves as a corrigendum to a prior article published in the same journal in 2019, as the authors found an error in the original ARVC risk calculator.
Clinical Topics: Arrhythmias and Clinical EP, Heart Failure and Cardiomyopathies, Prevention, Implantable Devices, Genetic Arrhythmic Conditions, SCD/Ventricular Arrhythmias, Atrial Fibrillation/Supraventricular Arrhythmias, Acute Heart Failure
Keywords: Arrhythmias, Cardiac, Arrhythmogenic Right Ventricular Dysplasia, Cardiomyopathies, Death, Sudden, Cardiac, Defibrillators, Implantable, Heart Failure, Primary Prevention, Risk Assessment, Risk Factors, Stroke Volume, Syncope, Tachycardia, Ventricular, Ventricular Function, Left
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