Cre/CysC ratio may predict muscle composition and is associated with glucose disposal ability and macrovascular disease in patients with type 2 diabetes

Author:

Yang Qing,Zhang Mei,Sun Peng,Li Yanying,Xu Huichao,Wang Kejun,Shen Hongshan,Ban Bo,Liu FupengORCID

Abstract

IntroductionSince the ratio of creatinine to cystatin C (Cre/CysC) can reflect muscle volume, it has been proven to be a predictor of sarcopenia in patients with or without diabetes. Here, we investigated the predictive value of Cre/CysC for the skeletal muscle composition and its correlations with glucose disposal ability and diabetic complications in patients with type 2 diabetes.Research design and methodsThe skeletal muscle index (SMI) and mean skeletal muscle attenuation (MMA) values of 193 patients with type 2 diabetes were obtained through analyses of CT images at the lumbar 3 level.ResultsSerum Cre/CysC was significantly correlated with both the SMI (r=0.375, p<0.001) and MMA (r=0.378, p<0.001). Multiple stepwise linear regression analysis demonstrated that Cre/CysC was the only biochemical predictor of the SMI (β=0.48 (95% CI 0.02 to 0.94)) and MMA (β=0.57 (95% CI 0.14 to 1.01)). Furthermore, the fat mass index (FMI) was significantly associated with the MMA (r=−0.481, p<0.001) but not the SMI (r=0.101, p=0.164). In the diabetic complications analysis, Cre/CysC was significantly lower in patients with cardiovascular disease (95% CI (−1.47 to –0.22), p=0.008) and lower extremity arterial disease (95% CI (−1.44 to –0.29), p=0.004). Moreover, in the 100 g steamed bun test, Cre/CysC was significantly correlated with glucose levels at 60 min (r=−0.162, p=0.045), 120 min (r=−0.287, p<0.001) and 180 min (r=−0.313, p<0.001).ConclusionsCre/CysC may be a valuable predictor of skeletal muscle composition in type 2 diabetes. Patients with a higher Cre/CysC may have a better ability to dispose of postprandial glucose and are at a lower risk of macrovascular disease.

Funder

Doctoral foundation of Affiliated Hospital of Jining Medical University

Publisher

BMJ

Subject

Endocrinology, Diabetes and Metabolism

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3