Are Multiparametric Risk Predictions Superior For Assessing HCM Patients?
The development of a multiparametric image-based risk prediction algorithm could be superior in predicting the composite endpoints for hypertrophic cardiomyopathy (HCM) compared with the current model based on conventional risk factors, according to an article published Dec. 7 in JACC: Heart Failure.
Georgios Georgiopoulos, MD, PHD, et al., performed a random-effect network meta-analysis on established studies published from 1955 to November 2020 to synthesize and compare the prognostic impact of demographic, clinical, biochemical and imaging finding in patients with HCM. The analysis included a total of 112 studies and 58,732 patients with HCM.
The analysis showed that increased brain natriuretic peptide/N-terminal pro–B-type natriuretic peptide, late gadolinium enhancement (LGE), positive genotype, impaired global longitudinal strain and presence of apical aneurysm conferred increased risk for the composite endpoint. LGE, reflecting myocardial fibrosis, had the highest prognostic value for all endpoints and composite outcomes.
The results supported the development of multiparametric risk prediction algorithms for refined risk stratification in HCM. A multiparametric imaging-based model appeared to be superior in predicting adverse clinical outcomes in patients with HCM compared with traditional markers.
The authors note that, to their knowledge, this is the first systematic review and network meta-analysis investigating the prognostic impact of multiple biochemical, clinical and imaging parameters for patients with HCM. Furthermore, this analysis “encourages a comprehensive approach to HCM risk prediction by combining established predictors with novel imaging, genotype, and laboratory markers.”
In an accompanying editorial comment, Steve R. Ommen, MD, FACC, states that “results such as those from the meta-analysis serve as the basis for further investigation,” and that could serve as foundational markers for future drug discovery efforts and help identify patients most likely to benefit from the therapies.
Clinical Topics: Heart Failure and Cardiomyopathies, Vascular Medicine, Acute Heart Failure, Heart Failure and Cardiac Biomarkers
Keywords: Demography, Risk Assessment, Drug Discovery, Aneurysm, Genotype, Algorithms, Fibrosis, Cardiomyopathies, Heart Failure, Cardiomyopathy, Hypertrophic, Gadolinium, Contrast Media, Prognosis, Natriuretic Peptide, Brain
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