【摘要】 目的:调查中老年2型糖尿病患者肌少症危险因素，并构建列线图模型。方法:采用便利抽样的方法，选取安徽省某三级甲等医院内分泌科2023年5月—2023年12月收治的2型糖尿病患者349例，对其进行问卷调查。采用单因素和多因素Logistic回归分析对2型糖尿病患者肌少症危险因素进行探讨，并构建可视化的风险预测模型。通过受试者工作特征(ROC)曲线下面积对模型预测效能进行了验证。结果:2型糖尿病患者肌少症的发生率为16.9%(59/349)。多因素分析结果显示，病程、每周锻炼次数、BMI、小腿围、匹兹堡睡眠质量指数(PSQI)得分、营养状态评估(MNA-SF)得分是2型糖尿病患者发生肌少症的影响因素。基于以上因素构建肌少症的风险预测模型，ROC曲线下面积为0.982[95%CI(0.968,0.995)];最佳临界值为0.366,灵敏度为0.966,特异度为0.934。H-L拟合优度检验显示，χ~2=2.446,P=0.964;Brier评分为0.036。结论:肌少症风险预测模型预测效能较好，可为医护人员进行临床决策提供参考。更多还原

【Abstract】 Objective: To investigate the risk factors of sarcopenia in middle-aged and elderly patients with type 2 diabetes and construct a nomogram model. Methods: In this cross-sectional study, a total of 349 patients with type 2 diabetes admitted from May 2023 to December 2023 in the Department of Endocrinology of a tertiary A-level hospital in Anhui Province were selected and investigated using questionnaires and convenient sampling. Univariate analysis and Logistic regression analysis were performed to explore the risk factors of sarcopenia in type 2 diabetes patients, and a visual risk prediction model was constructed. The prediction efficiency of the model was verified by the region under receiver operating characteristic(ROC) curve. Results: The incidence of sarcopenia in patients with type 2 diabetes was 16.9%(59/349). Multivariate logistic regression analysis showed that diabetes course, the number of exercises per week, BMI,calf girth, Pittsburgh Sleep Quality Index(PSQI) score, and Nutritional Status Assessment(MNA-SF) score were the influencing factors for the development of sarcopenia in patients with type 2 diabetes. According to these variables, a prediction model was constructed, and the area under the ROC curve was 0.982 [95%CI(0.968,0.995)]. The optimal critical value was 0.366,the sensitivity was 0.966,and the specificity was 0.934. The H-L test showed that χ~2=2.446,P=0.964,and Brier score was 0.036. Conclusion: The risk prediction model of sarcopenia is effective and can provide reference for clinical treatment.更多还原