A nomogram model combining sarcopenic obesity and biomarkers to predict the risk of vascular stiffness

IF 2.9 Q3 NUTRITION & DIETETICS

Clinical nutrition ESPEN Pub Date : 2025-07-16 DOI:10.1016/j.clnesp.2025.07.021

Wenwen Liu , Mingyu Zhu , Ziyi Wei , Ningxin Chen , Tingting Han , Ting Zhang , Yurong Weng , Yiling Fan , Yaomin Hu

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引用次数: 0

Abstract

Background & aims

Accumulating evidence reveals that sarcopenia and obesity display a close association with vascular aging. However, comprehensive analysis of the clinical model for estimating the risk of arterial stiffness based on the co-existence of sarcopenia and obesity has not yet been performed.

Methods

Here, we curated anthropometric, serological, clinical and computerized tomography (CT) variables from 1136 patients and applied univariate analysis (to eliminate irrelevant predictors) and logistic regression analysis (p < 0.05) in the development cohort to establish the clinical model. The precision of the model was evaluated through area under the curve (AUC) of receiver operator characteristic (ROC), calibration plot and decision curve analysis (DCA), for its discriminative power, calibration consistency and clinical usefulness.

Results

Logistic regression analysis identified that body mass index (BMI), total triglyceride (TG), interleukin-6 (IL-6), previous diabetes and hypertension, skeletal muscle fat index (SMFI) and skeletal muscle index (SMI) served as independent predictors for arterial stiffness and three clinical models based on these variables were constructed. The Model incorporating SMI and SMFI simultaneously (model ^{SMI + SMFI}), exhibited superior performance as compared to the models with only SMI (model ^SMI) or only SMFI (model ^SMFI), with reference to the discriminative power (ROC ^{SMI + SMFI} 0.795), calibrative ability (Eavg ^{SMI + SMFI} 0.022, Emax ^{SMI + SMFI} 0.041) and clinical utility in the validation cohort.

Conclusions

This research presents a model for the estimation of pulse wave velocity (PWV), which incorporates BMI, TG, IL-6, previous diabetes and hypertension, SMI and SMFI. The model incorporating sarcopenia and obesity simultaneously instead individually, predicts arterial stiffness more accurately. This advancement could enhance our understanding of the role of sarcopenic obesity in vascular dysfunction.

查看原文本刊更多论文

结合肌肉减少性肥胖和生物标志物预测血管僵硬风险的nomogram模型。

背景与目的：越来越多的证据表明，肌肉减少症和肥胖与血管老化密切相关。然而，基于肌少症和肥胖共存的动脉硬化风险评估的临床模型尚未得到全面分析。方法：在此，我们收集了1136例患者的人体测量学、血清学、临床和计算机断层扫描（CT）变量，并应用单因素分析（以消除不相关的预测因素）和逻辑回归分析(p)。Logistic回归分析发现，身体质量指数（BMI）、总甘油三酯（TG）、白细胞介素-6 （IL-6）、既往糖尿病和高血压、骨骼肌脂肪指数（SMFI）和骨骼肌指数（SMI）是动脉僵硬的独立预测因子，并基于这些变量构建了三个临床模型。同时纳入SMI和SMFI的模型（模型SMI+SMFI）在判别能力（ROC SMI+SMFI 0.795）、校准能力（Eavg SMI+SMFI 0.022、Emax SMI+SMFI 0.041）和临床应用方面均优于仅纳入SMI（模型SMI）或仅纳入SMFI（模型SMFI）的模型。结论：本研究建立了一个综合BMI、TG、IL-6、既往糖尿病和高血压、SMI和SMFI的脉搏波速度（PWV）估计模型。该模型将肌肉减少症和肥胖同时纳入，而不是单独纳入，可以更准确地预测动脉僵硬度。这一进展可以增强我们对肌肉减少性肥胖在血管功能障碍中的作用的理解。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Clinical nutrition ESPEN NUTRITION & DIETETICS-

CiteScore

4.90

自引率

3.30%

发文量

512

期刊介绍： Clinical Nutrition ESPEN is an electronic-only journal and is an official publication of the European Society for Clinical Nutrition and Metabolism (ESPEN). Nutrition and nutritional care have gained wide clinical and scientific interest during the past decades. The increasing knowledge of metabolic disturbances and nutritional assessment in chronic and acute diseases has stimulated rapid advances in design, development and clinical application of nutritional support. The aims of ESPEN are to encourage the rapid diffusion of knowledge and its application in the field of clinical nutrition and metabolism. Published bimonthly, Clinical Nutrition ESPEN focuses on publishing articles on the relationship between nutrition and disease in the setting of basic science and clinical practice. Clinical Nutrition ESPEN is available to all members of ESPEN and to all subscribers of Clinical Nutrition.