一种组合了sarcopenic肥胖和生物标志物的nomogram模型,以预测血管硬的风险
Wenwen Liu1, Mingyu Zhu1, Ziyi Wei1
1Department of Geriatrics, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai 200127, China.
Clinical nutrition ESPEN
|July 18, 2025
概括
萨尔科佩尼亚和肥胖症一起预测动脉硬性比单独更准确. 使用体重指数,甘油三,IL-6和其他因素的新临床模型改善了对血管衰老的风险估计.
科学领域:
- 血管衰老研究 血管衰老研究
- 临床诊断 临床诊断 临床诊断
- 肥胖和萨科佩尼研究的研究.
背景情况:
- 肉症和肥胖症与血管衰老有关.
- 在sarcopenic肥胖症中缺乏全面的临床模型来估计动脉硬的风险.
研究的目的:
- 开发和验证用于估计动脉硬风险的临床模型.
- 评估纳入萨尔科佩尼亚和肥胖指标的模型的预测性能.
主要方法:
- 精选了来自1136名患者的人类测量,血清学,临床和CT数据.
- 使用单变量和逻辑回归分析来识别预测因素.
- 使用ROC,校准图表和DCA验证模型性能.
主要成果:
- 确定了BMI,TG,IL-6,糖尿病,高血压,SMFI和SMI作为独立的预测因素.
- 结合SMI和SMFI (sarcopenia和肥胖指标) 的模型显示出优异的预测能力 (ROC 0.795).
- 组合模型显示出更好的校准和临床实用性.
结论:
- 结合BMI,TG,IL-6,糖尿病,高血压,SMI和SMFI的新型临床模型预测了动脉硬.
- 同时考虑缩症和肥胖症提供了比个人评估更准确的动脉硬性预测.
- 这种模型增强了对sarcopenic肥胖在血管功能障碍中的作用的理解.
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