Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Nutr Metab Cardiovasc Dis. 2023 Sep;33(9):1733-1739. doi: 10.1016/j.numecd.2023.05.031. Epub 2023 Jun 1.
Heart failure with concomitant sarcopenia has a poor prognosis; therefore, simple methods for evaluating the appendicular skeletal muscle mass index (ASMI) are required. Recently, a model incorporating anthropometric data and the sarcopenia index (i.e., serum creatinine-to-cystatin C ratio [Cre/CysC]), was developed to estimate the ASMI. We hypothesized that this model was superior to the traditional model, which uses only anthropometric data to predict prognosis. This retrospective cohort study compared the prognostic value of low ASMI as defined by the biomarker and anthropometric models in patients with heart failure.
Among 847 patients, we estimated ASMI using an anthropometric model (incorporating age, body weight, and height) in 791 patients and a biomarker model (incorporating age, body weight, hemoglobin, and Cre/CysC) in 562 patients. The primary outcome was all-cause mortality. Overall, 53.4% and 39.1% of patients were diagnosed with low ASMI (using the Asian Working Group for Sarcopenia cut-off) by the anthropometric and biomarker models, respectively. The two models showed a poor agreement in the diagnosis of low ASMI (kappa: 0.57, 95% confidence interval: 0.50-0.63). Kaplan-Meier curves showed that a low ASMI was significantly associated with all-cause death in both models. However, this association was retained after adjustment for other covariates in the biomarker model (hazard ratio: 2.32, p = 0.001) but not in the anthropometric model (hazard ratio: 0.79, p = 0.360).
Among patients hospitalized with heart failure, a low ASMI estimated using the biomarker model, and not the anthropometric model, was significantly associated with all-cause mortality.
伴有肌肉减少症的心力衰竭预后不良；因此，需要简单的方法来评估四肢骨骼肌质量指数（ASMI）。最近，开发了一种结合人体测量学数据和肌少症指数（即血清肌酐与胱抑素 C 比值 [Cre/CysC]）的模型来估计 ASMI。我们假设该模型优于仅使用人体测量学数据预测预后的传统模型。本回顾性队列研究比较了基于生物标志物和人体测量学模型定义的低 ASMI 对心力衰竭患者预后的预测价值。
在 847 例患者中，我们使用人体测量学模型（纳入年龄、体重和身高）在 791 例患者中估计 ASMI，使用生物标志物模型（纳入年龄、体重、血红蛋白和 Cre/CysC）在 562 例患者中估计 ASMI。主要结局是全因死亡率。总体而言，分别有 53.4%和 39.1%的患者被人体测量学和生物标志物模型诊断为低 ASMI（使用亚洲肌少症工作组的切点）。两种模型在低 ASMI 的诊断上显示出较差的一致性（kappa：0.57，95%置信区间：0.50-0.63）。Kaplan-Meier 曲线显示，在两种模型中，低 ASMI 均与全因死亡显著相关。然而，在校正生物标志物模型中的其他协变量后，这种相关性仍然存在（风险比：2.32，p=0.001），而在人体测量学模型中则不存在（风险比：0.79，p=0.360）。
在因心力衰竭住院的患者中，使用生物标志物模型而非人体测量学模型估计的低 ASMI 与全因死亡率显著相关。
