非肥胖2型糖尿病患者肌肉量减少危险因素的列线图预测模型研究  

Study on Nomogram Prediction Model for Risk Factors of Muscle Mass Loss in Non-obese Patients with Type 2 Diabetes

作　　者：张冰青 胡馨云 欧阳煜钦 向心月 汤文娟 冯文焕[1] ZHANG Bingqing;HU Xinyun;OUYANG Yuqin;XIANG Xinyue;TANG Wenjuan;FENG Wenhuan(Endocrine and Metabolic Disease Medical Center,Affiliated Drum Tower Hospital,Nanjing University of Chinese Medicine,Nanjing 210008,China;Department of Endocrinology,Nanjing Drum Tower Hospital,Affiliated Hospital of Medical School,Nanjing University,Nanjing 210008,China)

机构地区：[1]南京中医药大学鼓楼临床医学院内分泌与代谢疾病医学中心,江苏省南京市210008 [2]南京大学医学院附属鼓楼医院内分泌科,江苏省南京市210008

出　　处：《中国全科医学》2024年第33期4139-4146,共8页Chinese General Practice

基　　金：江苏省自然科学基金面上项目(BK20201115);中华国际交流基金会森美中华糖尿病科研基金(Z-2017-26-1902);南京市卫生科技发展专项资金项目(YKK23072)。

摘　　要：背景肌肉量减少能增加2型糖尿病(T2DM)患者高血糖及肌少症发生风险,中国成人T2DM以非肥胖者为主,这些患者较肥胖者更容易伴发肌肉量减少。目的建立个体化预测非肥胖T2DM患者肌肉量减少危险因素列线图预测模型。方法回顾性选取2018年1月—2023年9月南京大学医学院附属鼓楼医院内分泌科收治的非肥胖T2DM患者905例为研究对象,以简单随机抽样法按7∶3比例分为训练集(633例)和验证集(272例),收集两组患者的一般资料及临床指标并进行比较。根据多因素Logistic回归分析确定训练集肌肉量减少风险影响因素并构建列线图预测模型,采用受试者工作特征(ROC)曲线、Hosmer-Lemeshow校准曲线及临床决策曲线(DCA)评估列线图预测模型的预测价值和临床实用性。结果非肥胖T2DM患者肌肉量减少的患病率为42.3%(383/905)。训练集和验证集患者各项临床指标比较,差异均无统计学意义(P>0.05)。多因素Logistic回归分析结果显示,增龄(OR=1.039,95%CI=1.010~1.070,P=0.009)、男性(OR=3.425,95%CI=2.133~5.499,P<0.001)、BMI<23.5 kg/m^(2)(OR=19.678,95%CI=11.319~34.210,P<0.001)、糖化血红蛋白升高(OR=1.196,95%CI=1.081~1.323,P<0.001)、内脏脂肪面积增加(OR=1.021,95%CI=1.010~1.032,P<0.001)是非肥胖T2DM患者肌肉量减少的独立危险因素。列线图预测模型预测训练集和验证集患者肌肉量减少发生风险的ROC曲线下面积(AUC)分别为0.825(95%CI=0.793~0.856,P<0.001)和0.806(95%CI=0.753~0.859,P<0.001)。Hosmer-Lemeshow拟合优度检验结果显示,拟合度较好(训练集:χ^(2)=11.822,P=0.159;验证集:χ^(2)=8.189,P=0.415)。Bootstrap法绘制模型校准图显示校准曲线与标准曲线贴合良好。DCA曲线显示当患者阈值概率为0.06~0.94时,使用列线图预测模型预测T2DM患者发生肌肉量减少的发生风险更有益。结论增龄、男性、BMI<23.5 kg/m^(2)、糖化血红蛋白升高、内脏脂肪面积增加是非肥胖T2DM患者肌肉量Background Muscle mass loss increases the risk of hyperglycaemia and sarcopenia in patients with type 2diabetes mellitus(T2DM),and Chinese adults with T2DM are predominantly non-obese,who are more likely to be associated with muscle mass loss than the obese.Objective To establish an individualized Nomogram prediction model for the risk factors of muscle mass loss in non-obese patients with T2DM.Methods A retrospective study was conducted to select 905 non-obese patients with T2DM admitted to the Department of Endocrinology,Nanjing Drum Tower Hospital,Affiliated Hospital of Medical School,Nanjing University from January 2018 to September 2023.The patients were divided into a training set(n=633)and a validation set(n=272)using simple random sampling at a ratio of 7∶3,and the general data and clinical indexes of the two groups of patients were collected and compared.Multivariate Logistic regression analysis was performed to determine risk factors for muscle mass loss in the training set and a Nomogram prediction model was constructed.The predictive value and clinical utility of the Nomogram prediction model were evaluated using receiver operating characteristic(ROC)curve,Hosmer-Lemeshow calibration curve,and decision curve analysis(DCA),respectively.Results The prevalence of muscle mass loss in nonobese patients with T2DM was 42.3%(383/905).Comparison of the clinical indicators of the patients in the training and validation sets showed no statistically significant differences(P>0.05).Multivariate Logistic regression analysis showed that age(OR=1.039,95%CI=1.010-1.070,P=0.009),male(OR=3.425,95%CI=2.133-5.499,P<0.001),BMI<23.5 kg/m^(2)(OR=19.678,95%CI=11.319-34.210,P<0.001),elevated Hb A_(1c)(OR=1.196,95%CI=1.081-1.323,P<0.001),increased visceral fat area(OR=1.021,95%CI=1.010-1.032,P<0.001)were independent risk factors for muscle mass loss in non-obese patients with T2DM.The area under curve(AUC)of the ROC for the Nomogram prediction model to predict the risk of muscle mass loss occurring in patients in the training

关 键 词：糖尿病 2型 非肥胖 肌肉量减少 列线图 危险因素 

分 类 号：R587.1[医药卫生—内分泌]