Cardiac magnetic resonance imaging and computational modeling are needed to improve sudden cardiac death risk stratification in patients with nonischemic cardiomyopathy.
This review highlights the limitations of LVEF for predicting sudden cardiac death in nonischemic cardiomyopathy and proposes new risk stratification strategies including cardiac MRI and computational modeling.
Nonischemic cardiomyopathy (NICM) is common and patients are at significant risk for early mortality secondary to ventricular arrhythmias. Current guidelines recommend implantable cardioverter-defibrillator (ICD) therapy to decrease sudden cardiac death (SCD) in patients with heart failure and reduced left ventricular ejection fraction. However, in randomized clinical trials comprised solely of patients with NICM, primary prevention ICDs did not confer significant mortality benefit. Moreover, left ventricular ejection fraction has limited sensitivity and specificity for predicting SCD. Therefore, precise risk stratification algorithms are needed to define those at the highest risk of SCD. This review examines mechanisms of sudden arrhythmic death in patients with NICM, discusses the role of ICD therapy and treatment of heart failure for prevention of SCD in patients with NICM, examines the role of cardiac magnetic resonance imaging and computational modeling for SCD risk stratification, and proposes new strategies to guide future clinical trials on SCD risk assessment in patients with NICM.
Chrispin et al. (Tue,) conducted a review in Nonischemic cardiomyopathy. Risk stratification algorithms was evaluated. Cardiac magnetic resonance imaging and computational modeling are needed to improve sudden cardiac death risk stratification in patients with nonischemic cardiomyopathy.
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