Risk stratification for ventricular arrhythmias and sudden cardiac death in arrhythmogenic right ventricular
Julia Cadrin-Tourigny1, Laurens P Bosman2, Rafik Tadros1
1Department of Medicine, Montreal Heart Institute , Montreal , Quebec , Canada.
Insights
Arrhythmogenic right ventricular cardiomyopathy (ARVC) risk stratification is improving. Recent findings consolidate predictors for ventricular arrhythmias and sudden cardiac death, informing implantable cardioverter-defibrillator (ICD) decisions.
Area of Science:
- Cardiology
- Genetics
- Electrophysiology
Background:
- Arrhythmogenic right ventricular cardiomyopathy (ARVC) is a genetic heart condition.
- It carries a high risk of ventricular arrhythmias and sudden cardiac death (SCD).
- Implantable cardioverter-defibrillators (ICDs) are crucial for prevention.
Purpose of the Study:
- To review current evidence on risk stratification in ARVC patients.
- To highlight recent advancements in identifying predictors of adverse arrhythmic events.
- To discuss the integration of risk predictors into clinical guidelines and decision-making.
Main Methods:
- Systematic review of recent literature and meta-analyses.
- Analysis of expert consensus documents and management guidelines.
- Evaluation of a novel risk prediction model for ARVC.
Main Results:
- Recent meta-analyses identified key predictors of ventricular arrhythmias in ARVC.
- Updated guidelines incorporate these predictors for ICD recommendations.
- A risk prediction model enables individualized risk assessment for ICD implantation.
Conclusions:
- Risk prediction knowledge for ARVC has significantly advanced.
- Further research may incorporate exercise and specific surrogate outcomes for SCD.
- Refined risk stratification aids in shared decision-making for ICDs in ARVC.
Abstract:
Introduction: Arrhythmogenic right ventricular cardiomyopathy (ARVC) is a genetically determined disease associated with a significant risk of ventricular arrhythmias and sudden cardiac death (SCD). Implantable cardioverter-defibrillators (ICDs) are the only effective preventive measure. Over the past 30 years, much effort has been invested in determining predictors of adverse arrhythmic events in these patients. Areas covered: This review summarizes available evidence on risk stratification for ARVC, with an emphasis on recent research findings. While efforts are ongoing to define risk predictors, several recent publications have synthetized and built on this knowledge base. A recently published meta-analysis has clarified the strongest predictors of ventricular arrhythmias in ARVC, which vary depending on the population included. Three management guidelines/expert consensus documents have integrated the previously described risk predictors into proposed ICD recommendations. Furthermore, a risk prediction model has allowed the integration of multiple risk factors to provide individualized risk prediction and to inform shared-decision making regarding ICD implantation. Expert opinion: Over the past few years, knowledge of risk prediction in ARVC has been consolidated and refined. Further improvements may be made by the considering additional predictors such as exercise and by targeting more specific surrogate outcomes for SCD.
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