葡萄糖变异参数构建糖尿病周围神经病变风险预测模型的探讨  

Development and Validation of Risk Predicting Model for Severe Diabetic Peripheral Neuropathy Based on Glucose Variability Parameters

作　　者：张帆[1] 郭伟昌[1] 谭洪[1] 殷和佳 彭露萍 赵燕[1] 李会芳[1] ZHANG Fan;GUO Weichang;TAN Hong;YIN Hejia;PENG Luping;ZHAO Yan;LI Huifang(The 2nd Dept.of Endocrinology,The 1st Affiliated Hospital of Kunming Medical University,Kunming Yunnan 650032,China)

机构地区：[1]昆明医科大学第一附属医院内分泌二科,云南昆明650032

出　　处：《昆明医科大学学报》2023年第5期53-59,共7页Journal of Kunming Medical University

基　　金：国家自然科学基金资助项目(82160165);云南省“兴滇英才”名医专项基金资助项目(RLMY20220009);云南省中青年学术和技术带头人后备人才基金资助项目(202105AC160093);昆明医科大学科技创新团队基金资助项目(CXTD202101);云南省代谢性疾病临床医学研究中心子课题基金资助项目(202102AA100056)。

摘　　要：目的 使用葡萄糖变异参数建立2型糖尿病患者重度DPN发生的临床风险预测模型并进行验证,为糖尿病慢性并发症的防治提供参考依据。方法 收集2019年4月至2020年5月昆明医科大学第一附属医院内分泌二科住院治疗且符合纳入标准的2型糖尿病周围神经病变患者323例的临床资料。据感觉阈值测定结果将患者分为重度糖尿病周围神经病变(DPN)组及非重度组。使用Lasso回归模型筛选重度DPN发生的预测因子,制作列线图使模型可视化,做ROC曲线、校准度曲线、决策曲线评估模型区分度、校准度及辅助模型临床决策。结果 2型糖尿病患者重度DPN发生的显著预测因素为年龄、吸烟、血脂异常、HbA1c、TIR,同时TIR是重度DPN发生的独立危险因素;使用筛选变量建立重度DPN的预测模型。ROC曲线评估模型区分度AUC=0.647(95%CI=0.585~0.708,P <0.05);HL拟合优度检验评估模型拟合度P=0.074。结论 葡萄糖变异参数中的TIR能够作为2型糖尿病患者重度DPN发生的显著预测因子,以TIR为基础建立的临床预测模型准确性尚可;建议患者经模型评估重度DPN发生风险大于20%(评分> 250)即进行积极干预。Objective To develop and validate a risk prediction model for severe DPN in patients with type 2 diabetes using glucose variability parameters,and to provide the evidence for the prevention and treatment of diabetic chronic complications.Methods The medical records from 323 inpatients with T2DM who met the inclusion criteria were collected in the First Affiliated Hospital of Kunming Medical University from April 2019 to May 2020.Based on the professional sensory threshold measured,patients were divided into none-sever DPN group and severe DPN group.Lasso regression model was used to select risk factors.A risk prediction models for severe DPN was established and shown as a nomogram.ROC curve,calibration curve and decision curve analysis was used to validate the model.Results Age,smoking,dyslipidemia,HbA1c and TIR were significant predictors of severe DPN in type 2 diabetes patients,and TIR was an independent risk factor for severe DPN.An assessing model discrimination was established by using ROC curves with AUC=0.653(95%CI=0.592-0.715,P<0.05).The Hosmer-Lemeshow test was used to determine the model fit with P value 0.074.Conclusion TIR can be a significant predictor of the severe DPN in patients with T2DM,and the clinical prediction model established on the basis of TIR has the fair accuracy.It is recommended to actively intervene in the patients with a risk of severe DPN greater than 20%(score>250)evaluated by the model.

关 键 词：2型糖尿病 糖尿病变异参数 糖尿病周围神经病变 

分 类 号：R587.1[医药卫生—内分泌]