Frontiers in cardiovascular medicine · 2026
Risk stratification for sudden cardiac death in nonischemic dilated cardiomyopathy: a moving target?
СтатьяОбзорНазвание и аннотация: Перевод в очереди
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Bradel Laura, Kovrizhkin Katherine, Yacoub Harout, Turitto Gioia
Аннотация
Risk stratification for sudden cardiac death (SCD) in non-ischemic dilated cardiomyopathy (NICM) and a left ventricular ejection fraction (LVEF) ≤35%. remains controversial. The value of a low LVEF alone is limited, as it cannot distinguish between arrhythmic and nonarrhythmic mortality. This led to further investigation into markers of electrical instability. Prior studies have evaluated noninvasive and invasive markers, including ambient arrhythmias, signal-averaged ECG, QT dispersion, T-wave alternans, heart rate variability, and programmed ventricular stimulation. None of these markers have consistently improved the predictive accuracy for SCD beyond LVEF. Cardiac magnetic resonance (CMR) imaging with late gadolinium enhancement (LGE) has emerged as a tool for substrate characterization, with myocardial fibrosis burden and LGE patterns associated with SCD, arrhythmic events, as well as appropriate therapies in patients with implantable cardioverter-defibrillators. Quantitative LGE thresholds and integrated CMR-based models may enhance SCD risk discrimination, although methodological heterogeneity, scanner-dependent quantification, and lack of randomized trials challenge the inclusion of CMR parameters in current guidelines. Emerging tiered approaches like the ReCONSIDER framework, combining noninvasive markers, CMR tissue characterization, and electrophysiologic testing to capture the heterogeneity of NICM, may also be of value. However, at the present time, no single imaging, clinical, or electrophysiologic marker has achieved guideline-level validation as an adjunct or a replacement for LVEF. Future studies may focus on standardizing CMR acquisition and quantification, prospective validation of multimodal risk models, and assessment of dynamic, serial biomarkers to establish a more accurate approach to SCD risk stratification in NICM.