Risk stratification for sudden cardiac death in nonischemic dilated cardiomyopathy: a moving target?
Laura Bradel1,2, Katherine Kovrizhkin3, Harout Yacoub1,2
1Department of Medicine, NewYork-Presbyterian Brooklyn Methodist Hospital, Brooklyn, NY, United States.
Insights
Risk stratification for sudden cardiac death (SCD) in non-ischemic dilated cardiomyopathy (NICM) is challenging. Current markers, including left ventricular ejection fraction (LVEF), are insufficient; novel imaging and integrated approaches are needed for better prediction.
Area of Science:
- Cardiology
- Medical Imaging
- Electrophysiology
Background:
- Risk stratification for sudden cardiac death (SCD) in non-ischemic dilated cardiomyopathy (NICM) with left ventricular ejection fraction (LVEF) ≤35% remains controversial.
- Low LVEF alone is insufficient for distinguishing arrhythmic from nonarrhythmic mortality, necessitating investigation into electrical instability markers.
Purpose of the Study:
- To review current and emerging strategies for SCD risk stratification in NICM.
- To evaluate the role of Cardiac Magnetic Resonance (CMR) imaging with late gadolinium enhancement (LGE) and integrated multimodal approaches.
Main Methods:
- Review of prior studies evaluating noninvasive and invasive markers for SCD prediction.
- Assessment of Cardiac Magnetic Resonance (CMR) imaging, specifically late gadolinium enhancement (LGE), for myocardial fibrosis characterization.
- Evaluation of emerging tiered approaches combining clinical, imaging, and electrophysiologic data.
Main Results:
- No single noninvasive or invasive marker has consistently improved SCD prediction beyond LVEF.
- CMR-LGE shows association with SCD and arrhythmic events, but methodological heterogeneity limits current guideline inclusion.
- Emerging multimodal frameworks show promise but lack guideline-level validation.
Conclusions:
- Current markers, including LVEF and traditional electrophysiologic tests, are inadequate for precise SCD risk stratification in NICM.
- Standardization of CMR quantification and prospective validation of multimodal risk models are crucial for future advancements.
- Accurate SCD risk stratification in NICM requires further research into standardized imaging, serial biomarkers, and integrated predictive models.
Abstract:
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.
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