Development and validation of a risk prediction model for diabetic retinopathy in type 2 diabetic patients

作者全名："Zhu, Chengjun; Zhu, Jiaxi; Wang, Lei; Xiong, Shizheng; Zou, Yijian; Huang, Jing; Xie, Huimin; Zhang, Wenye; Wu, Huiqun; Liu, Yun"

作者地址："[Zhu, Chengjun; Zhu, Jiaxi; Wang, Lei; Xiong, Shizheng; Zou, Yijian; Huang, Jing; Xie, Huimin; Zhang, Wenye; Wu, Huiqun] Nantong Univ, Dept Med Informat, Med Sch, Nantong 226001, Jiangsu, Peoples R China; [Wang, Lei] Chongqing Med Univ, Coll Med Informat, Chongqing 400016, Peoples R China; [Liu, Yun] Nanjing Med Univ, Affiliated Hosp 1, Dept Informat, 300 Guang Zhou Rd, Nanjing 210029, Jiangsu, Peoples R China"

通信作者："Wu, HQ (通讯作者)，Nantong Univ, Dept Med Informat, Med Sch, Nantong 226001, Jiangsu, Peoples R China.; Liu, Y (通讯作者)，Nanjing Med Univ, Affiliated Hosp 1, Dept Informat, 300 Guang Zhou Rd, Nanjing 210029, Jiangsu, Peoples R China."

来源：SCIENTIFIC REPORTS

ESI学科分类：Multidisciplinary

WOS号：WOS:000984094500017

JCR分区：Q1

影响因子：3.8

年份：2023

卷号：13

期号：1

开始页：　

结束页：　

文献类型：Article

关键词：　

摘要："To establish a risk prediction model and make individualized assessment for the susceptible diabetic retinopathy (DR) population in type 2 diabetic mellitus (T2DM) patients. According to the retrieval strategy, inclusion and exclusion criteria, the relevant meta-analyses on DR risk factors were searched and evaluated. The pooled odds ratio (OR) or relative risk (RR) of each risk factor was obtained and calculated for beta coefficients using logistic regression (LR) model. Besides, an electronic patient-reported outcome questionnaire was developed and 60 cases of DR and non-DR T2DM patients were investigated to validate the developed model. Receiver operating characteristic curve (ROC) was drawn to verify the prediction accuracy of the model. After retrieving, eight meta-analyses with a total of 15,654 cases and 12 risk factors associated with the onset of DR in T2DM, including weight loss surgery, myopia, lipid-lowing drugs, intensive glucose control, course of T2DM, glycated hemoglobin (HbA1c), fasting plasma glucose, hypertension, gender, insulin treatment, residence, and smoking were included for LR modeling. These factors, followed by the respective beta coefficient was bariatric surgery (- 0.942), myopia (- 0.357), lipid-lowering drug follow-up < 3y (- 0.994), lipid-lowering drug follow-up > 3y (- 0.223), course of T2DM (0.174), HbA1c (0.372), fasting plasma glucose (0.223), insulin therapy (0.688), rural residence (0.199), smoking (- 0.083), hypertension (0.405), male (0.548), intensive glycemic control (- 0.400) with constant term alpha (- 0.949) in the constructed model. The area under receiver operating characteristic curve (AUC) of the model in the external validation was 0.912. An application was presented as an example of use. In conclusion, the risk prediction model of DR is developed, which makes individualized assessment for the susceptible DR population feasible and needs to be further verified with large sample size application."

基金机构："National Key R&D Program of China [2018YFC1314900, 2018YFC1314902]; Science and Technology Project of Nantong City [MS12020037]; Postgraduate Research & Practice Innovation Program of Jiangsu Province [KYCX22_3363]; Jiangsu Students' Platform for innovation and entrepreneurship training program [202210304122Y]"

基金资助正文："This work was supported by the grant from National Key R & D Program of China (2018YFC1314900, 2018YFC1314902), Science and Technology Project of Nantong City (No.MS12020037), Postgraduate Research & Practice Innovation Program of Jiangsu Province (No. KYCX22_3363), Jiangsu Students' Platform for innovation and entrepreneurship training program (No. 202210304122Y)."