1st Department of Cardiology, Aristotle University of Thessaloniki, Thessaloniki, Greece.
Department of Cardiology, West Hertfordshire Hospitals NHS Trust, Watford, United Kingdom.
JACC Cardiovasc Imaging. 2024 May;17(5):489-497. doi: 10.1016/j.jcmg.2023.07.005. Epub 2023 Aug 23.
Quantitative late gadolinium enhancement (LGE) cardiac magnetic resonance provides important prognostic information for sudden cardiac death (SCD) in hypertrophic cardiomyopathy (HCM). However, it has not been fully integrated into clinical practice.
The purpose of this study was to assess the prognostic value of LGE extent in predicting SCD in adults with HCM across different methods of quantification, thresholds, and patients' clinical profile.
The authors searched PubMed, Web of Science, and Cochrane Library for studies investigating the prognostic value of LGE% in predicting SCD in HCM. Pooled ORs were calculated with 95% CIs. The optimal threshold was determined using a multiple cutoffs model.
Eleven studies were included in the meta-analysis with a total of 5,550 patients and a median follow-up time of 5.2 years. Two studies quantified LGE manually, 7 studies used the 6 SD technique, 1 study used the 4 SD technique, and 1 study the 2 SD technique. There was no statistically significant difference in predicting SCD between these 4 methods (P = 0.443). Optimal cutoff could be determined only for the 6 SD technique. LGE 10% was the optimal threshold of the 6 SD technique with sensitivity 0.73 and specificity 0.67.
The different LGE quantification techniques have comparable accuracy in predicting SCD. When the more extensively studied 6 SD technique is used, LGE 10% is the optimal cutoff and can effectively restratify intermediate-risk patients. LGE extent can improve HCM risk stratification, but it is unlikely to become a standalone tool.
定量延迟钆增强(LGE)心脏磁共振为肥厚型心肌病(HCM)中的心脏性猝死(SCD)提供了重要的预后信息。然而,它尚未完全纳入临床实践。
本研究旨在评估 LGE 范围在不同量化方法、阈值和患者临床特征下预测 HCM 患者 SCD 的预后价值。
作者检索了 PubMed、Web of Science 和 Cochrane Library 中研究 LGE%预测 HCM 中 SCD 预后价值的研究。使用 95%CI 计算汇总 OR。使用多截止值模型确定最佳截止值。
共有 11 项研究纳入荟萃分析,共纳入 5550 例患者,中位随访时间为 5.2 年。其中 2 项研究手动量化 LGE,7 项研究使用 6SD 技术,1 项研究使用 4SD 技术,1 项研究使用 2SD 技术。这 4 种方法预测 SCD 时无统计学差异(P = 0.443)。仅能为 6SD 技术确定最佳截止值。对于 6SD 技术,LGE 10%是最佳阈值,其敏感性为 0.73,特异性为 0.67。
不同的 LGE 量化技术在预测 SCD 方面具有相当的准确性。当使用研究更为广泛的 6SD 技术时,LGE 10%是最佳截止值,可有效重新分层中危患者。LGE 范围可改善 HCM 风险分层,但不太可能成为独立工具。