Sun S Y, Gui W W, Jia C F, Pan Q Q, Lin X H, Zheng F P, Li H
Department of Endocrinology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310016, China.
Zhonghua Nei Ke Za Zhi. 2023 Feb 1;62(2):169-175. doi: 10.3760/cma.j.cn112138-20220511-00360.
To investigate the risk factors of diabetic nephropathy (DN) in primary type 2 diabetes mellitus (T2DM) patients and to quantitatively analyze the risk of DN by nomogram modeling. A total of 1 588 primary T2DM patients from 17 townships and streets in Zhejiang Province were enrolled from June 2018 to August 2018 in this cross-sectional study, with an average age of (56.8±10.1) years (50.06% male) and a mean disease duration of 9 years. The clinical data, biochemical test results, and fundus photographs of all T2DM patients were collected, and logistic regression analysis was used to screen the risk factors of DN. Then, a nomogram model was used to quantitatively analyze the risk of DN. DN occurred in 27.71% (440/1 588 cases) primary type 2 diabetes patients. Hemoglobin A (HbA) (=1.159, 95% 1.039-1.292), systolic blood pressure (=1.041, 95% 1.031-1.051), serum creatinine (Scr) (=1.011, 95% 1.004-1.017), serum globulin (GLOB) (=1.072, 95% 1.039-1.105), diabetic retinopathy (DR) (=1.463, 95% 1.073-1.996), education level of more than junior high school (=2.018, 95% 1.466-2.777), and moderate-intensity exercise (=0.751, 95% 0.586-0.961) were influencing factors of DN. Nomogram model analysis showed that the total score of each factor of DN ranged from 64-138 points, and the corresponding risk rate ranged from 0.1-0.9. The nomogram model also predicted a C-index value of 0.753 (95% 0.726-0.781) and an area under the receiver operating characteristic curve of DN of 0.753. Internal verification of the C-index reached 0.738. The model displayed medium predictive power and could be applied in clinical practice. HbA, systolic blood pressure, Scr, GLOB, DR, and more than a junior high school education are independent risk factors of DN. Nomogram modeling can more intuitively evaluate the risk of DN in primary T2DM patients.
探讨原发性2型糖尿病(T2DM)患者糖尿病肾病(DN)的危险因素,并通过列线图模型定量分析DN风险。本横断面研究于2018年6月至2018年8月纳入浙江省17个乡镇和街道的1588例原发性T2DM患者,平均年龄(56.8±10.1)岁(男性占50.06%),平均病程9年。收集所有T2DM患者的临床资料、生化检验结果及眼底照片,采用logistic回归分析筛选DN的危险因素。然后,使用列线图模型定量分析DN风险。1588例原发性2型糖尿病患者中,27.71%(440例)发生DN。糖化血红蛋白(HbA)(=1.159,95%可信区间1.039 - 1.292)、收缩压(=1.041,95%可信区间1.031 - 1.051)、血清肌酐(Scr)(=1.011,95%可信区间1.004 - 1.017)、血清球蛋白(GLOB)(=1.072,95%可信区间1.039 - 1.105)、糖尿病视网膜病变(DR)(=1.463,95%可信区间1.073 - 1.996)、初中以上文化程度(=2.018,95%可信区间1.466 - 2.77)和中等强度运动(=0.751,95%可信区间0.586 - 0.961)是DN的影响因素。列线图模型分析显示,DN各因素总分在64 - 138分之间,相应风险率在0.1 - 0.9之间。列线图模型预测的C指数值为0.字串95%可信区间0.726 - 0.781),DN的受试者工作特征曲线下面积为0.753。C指数内部验证达到0.738。该模型显示出中等预测能力,可应用于临床实践。HbA、收缩压、Scr、GLOB、DR和初中以上文化程度是DN的独立危险因素。列线图建模可以更直观地评估原发性T2DM患者发生DN的风险。