Role of late gadolinium enhancement in the risk stratification of pediatric hypertrophic cardiomyopathy: based on a Chinese cohortResearch in context - Xingrui Chen; Wei Xiangli; Xuan Ma; Yun Tang; Jiaxin Wang; Zhixiang Dong; Kankan Zhao; Zhuxin Wei; Xi Jia; Pengyu Zhou; Yujie Liu; Yanyan Song; et al. (The Lancet Regional Health. Western Pacific)
Summary: Background: Recently, late gadolinium enhancement (LGE) has been identified as an important risk factor in pediatric hypertrophic cardiomyopathy (HCM). However, its prognostic significance in pediatric HCM remains to be fully validated, particularly in Asian population. This study aims to assess the prognostic value of LGE and explore its incremental utility in predicting sudden cardiac death (SCD) in pediatric HCM using data from a Chinese cohort. Methods: 231 primary HCM patients ≤18 years of age with cardiac magnetic resonance (CMR) were retrospectively and consecutively enrolled in a single center. The composite outcomes included SCD or equivalent events and heart failure-related events. Findings: Of 231 patients (median age 15, IQR: 12–16), LGE was present in 195 (84.4%) with a median LGE extent of 4.7% (IQR: 2.0%–9.2%). During a median follow-up of 62 months (IQR: 39–85), 26 (11.3%) patients reached composite outcomes, and 13 (5.6%) patients experienced SCD events. Kaplan–Meier analysis showed a significantly increased risk of composite outcomes (log-rank P < 0.001) and SCD (log-rank P < 0.001) in the group with LGE extent ≥5%. In multivariable Cox analysis adjusted by clinical and imaging factors, LGE extent was independently associated with composite outcomes (adjusted HR: 1.15; P < 0.001) and SCD (adjusted HR: 1.11; P = 0.009). For SCD events, the addition of LGE extent could improve the model performance of HCM Risk-Kids model (C-statistics: 0.65 versus 0.79, P = 0.015) and PRIMaCY model (C-statistics: 0.62 versus 0.82, P = 0.002), respectively. Interpretation: In Chinese pediatric HCM, LGE serves as a risk factor in predicting adverse outcomes and may enhance SCD risk stratification strategies. Funding: This study was funded by the National Key Research and Development Program of China (2021YFF0501400 and 2021YFF0501404), the Key Project of the National Natural Science Foundation of China (82430066), and the Yunnan Province Science and Technology Platform and Talent Project (202305AF150033).