Comparison of Demographic, Clinical, Biochemical, and Imaging Findings in Hypertrophic Cardiomyopathy Prognosis: A Network Meta-Analysis

Abstract

Background: Despite hypertrophic cardiomyopathy (HCM) being the most common inherited heart disease and conferring increased risk for heart failure (HF) and sudden cardiac death (SCD), risk assessment in HCM patients is still largely unresolved. Objectives: This study aims to synthesize and compare the prognostic impact of demographic, clinical, biochemical, and imaging findings in patients with HCM. Methods: The authors searched PubMed, Embase, and Cochrane Library for studies published from 1955 to November 2020, and the endpoints were: 1) all-cause death; 2) an arrhythmic endpoint including SCD, sustained ventricular tachycardia, ventricular fibrillation, or aborted SCD; and 3) a composite endpoint including (1) or (2) plus hospitalization for HF or cardiac transplantation. The authors performed a pairwise meta-analysis obtaining the pooled estimate separately for the association between baseline variables and study endpoints. A random-effects network meta-analysis was subsequently used to comparatively assess the prognostic value of outcome associates. Results: A total of 112 studies with 58,732 HCM patients were included. Among others, 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. At network meta-analysis, LGE showed the highest prognostic value for all endpoints and was superior to all other associates except New York Heart Association functional class >class II. A multiparametric imaging-based model was superior in predicting the composite endpoint compared to a prespecified model based on conventional risk factors. Conclusions: This network meta-analysis supports the development of multiparametric risk prediction algorithms, including advanced imaging markers additively to conventional risk factors, for refined risk stratification in HCM.