Shiroma Kaori, Tanabe Hayato, Takiguchi Yoshinori, Yamaguchi Mizuki, Sato Masahiro, Saito Haruka, Tanaka Kenichi, Masuzaki Hiroaki, Kazama Junichiro J, Shimabukuro Michio
Department of Diabetes, Endocrinology, and Metabolism, Fukushima Medical University School of Medicine, Fukushima, Japan.
Department of Health and Nutrition, Faculty of Health and Nutrition, Okinawa University, Okinawa, Japan.
Front Nutr. 2023 Feb 1;10:1087471. doi: 10.3389/fnut.2023.1087471. eCollection 2023.
There are few reports evaluating the relationship between undernutrition and the risk of sarcopenia in type 2 diabetes mellitus (T2DM) patients.
We investigated whether undernutritional status assessed by the geriatric nutritional risk index (GNRI) and controlling nutritional status (CONUT) were associated with the diagnosis of sarcopenia.
This was a cross-sectional study of Japanese individuals with T2DM. Univariate or multivariate logistic regression analysis was performed to assess the association of albumin, GNRI, and CONUT with the diagnosis of sarcopenia. The optimal cut-off values were determined by the receiver operating characteristic (ROC) curve to diagnose sarcopenia.
In 479 individuals with T2DM, the median age was 71 years [IQR 62, 77], including 264 (55.1%) men. The median duration of diabetes was 17 [11, 23] years. The prevalence of sarcopenia was 41 (8.6%) in all, 21/264 (8.0%) in men, and 20/215 (9.3%) in women. AUCs were ordered from largest to smallest as follows: GNRI > albumin > CONUT. The cut-off values of GNRI were associated with a diagnosis of sarcopenia in multiple logistic regression analysis (odds ratio 9.91, 95% confidential interval 5.72-17.2), < 0.001. The superiority of GNRI as compared to albumin and CONUT for detecting sarcopenia was also observed in the subclasses of men, women, body mass index (BMI) < 22, and BMI ≥ 22.
Results showed that GNRI shows a superior diagnostic power in the diagnosis of sarcopenia. Additionally, its optimal cut-off points were useful overall or in the subclasses. Future large and prospective studies will be required to confirm the utility of the GNRI cut-off for undernutrition individuals at risk for sarcopenia.
评估2型糖尿病(T2DM)患者营养不良与肌肉减少症风险之间关系的报告较少。
我们调查了通过老年营养风险指数(GNRI)和控制营养状况(CONUT)评估的营养不足状态是否与肌肉减少症的诊断相关。
这是一项对日本T2DM患者的横断面研究。进行单变量或多变量逻辑回归分析,以评估白蛋白、GNRI和CONUT与肌肉减少症诊断的相关性。通过受试者工作特征(ROC)曲线确定诊断肌肉减少症的最佳临界值。
在479例T2DM患者中,中位年龄为71岁[四分位间距62, 77],其中男性264例(55.1%)。糖尿病中位病程为17[11, 23]年。肌肉减少症的总体患病率为41例(8.6%),男性为21/264例(8.0%),女性为20/215例(9.3%)。曲线下面积(AUC)从大到小排序如下:GNRI>白蛋白>CONUT。在多变量逻辑回归分析中,GNRI的临界值与肌肉减少症的诊断相关(优势比9.91,95%置信区间5.72 - 17.2),P<0.001。在男性、女性、体重指数(BMI)<22和BMI≥22的亚组中,也观察到GNRI在检测肌肉减少症方面优于白蛋白和CONUT。
结果表明,GNRI在肌肉减少症的诊断中显示出卓越的诊断能力。此外,其最佳临界点在总体或亚组中均有用。未来需要进行大规模前瞻性研究,以确认GNRI临界值对有肌肉减少症风险的营养不良个体的实用性。