摘要
背景糖尿病视网膜病变(DR)发病率高,危害性大,是导致成人失明的主要原因,但社区实施眼底筛查较为困难,而DR风险预测模型可帮助全科医生早期识别DR高危人群。目的探讨社区门诊就诊的2型糖尿病患者发生DR的危险因素,构建并验证DR风险预测模型,进一步提高DR患者筛查效率。方法收集2018年6月-2019年6月于方庄社区卫生服务中心门诊就诊的421例2型糖尿病患者,采用随机数字表法分为模型组336例,检验组85例。收集患者的一般资料,血压以及空腹血糖(FBG)、餐后2 h血糖、糖化血红蛋白(Hb A1c)、血肌酐、尿素氮、总胆固醇(TC)、三酰甘油(TG)、低密度脂蛋白胆固醇(LDL-C)及尿蛋白,均行非散瞳眼底彩色照相(NMFCS)。模型组采用单因素Logistic回归分析计算出发生DR的相关因素,得出的相关因素用多因素Logistic回归分析进一步探讨,在此基础上构建DR风险预测模型,并由检验组评估DR风险预测模型的可行性。结果在421例2型糖尿病患者中DR患者共87例,其中模型组69例,检验组18例。多因素Logistic回归分析结果显示,DR的危险因素有病程(β=0.196,OR=1.217,P<0.001),收缩压(SBP)(β=0.028,OR=1.028,P=0.038),FBG(β=0.409,OR=1.506,P=0.003),Hb A1c(β=0.594,OR=1.811,P=0.001),LDL-C(β=0.360,OR=1.434,P=0.038)。据此,构建的DR风险预测模型为Y=1/[1+e-(0.196X1+0.028X2+0.409X3+0.594X4+0.360X5-16.482)],其中,Y指DR发生概率,X1指病程,X2指SBP,X3指FBG,X4指Hb A1c,X5指LDL-C。DR风险预测模型预测模型组发生DR的ROC曲线下面积是0.884,诊断临界值是0.192。DR风险预测模型预测检验组发生DR的ROC曲线下面积是0.803,灵敏度为72.2%,特异度为79.1%。结论糖尿病患者的病程、SBP、FBG、HbA1c、LDL-C与DR显著相关,DR风险预测模型对DR有一定的预测价值。
Background Diabetic retinopathy(DR) has a high incidence and is a leading cause of blindness in adults.Although it is difficult to perform fundus screening in a wide range of population in communities,the risk prediction model of DR can help general practitioners identify high risk population of DR at an early stage.Therefore,carrying out the research on the risk prediction model for DR is particularly important.Objective To explore the risk factors of DR in type 2 diabetic outpatients in community settings,and use them to establish and verify a risk prediction model for DR,further improving the screening efficiency of DR.Methods From June 2018 to June 2019,421 type 2 diabetic outpatients from Fangzhuang Community Health Service Center were invited and were divided into model group(336 cases) and verification group(85 cases) by a table of random numbers.Demographic information,blood pressure,fasting blood glucose(FBG),2-h postprandial blood glucose,glycosylated hemoglobin(HbA1c),serum creatinine,urea nitrogen,total cholesterol(TC),triacylglycerol(TG),lowdensity lipoprotein cholesterol(LDL-C),urine protein,and results of non-mydriatic fundus color photography(NMFCS) of the patients were collected.Univariate Logistic regression analysis was used to identify DR-related factors in model group,and the related factors obtained were discussed with multivariate Logistic regression analysis to explore the risk factors of DR based on which the DR risk prediction model was constructed,and the feasibility of this prediction model was evaluated in the verification group.Results Altogether,87 patients were found with DR,including 69 in the model group and 18 in the verification group.Multivariate Logistic regression analysis showed that years of having T2 DM(β=0.196,OR=1.217,P<0.001),systolic blood pressure(β=0.028,OR=1.028,P=0.038),FBG(β=0.409,OR=1.506,P=0.003),Hb A1 c(β=0.594,OR=1.811,P=0.001) and LDL-C (β=0.360,OR=1.434,P=0.038) were risk factors of DR in type 2 diabates patients.Therefore,the DR risk prediction model was Y=1/[1+e-(0.196 X1+0.028 X2+0.409 X3+0.594 X4+0.360 x5-16.482)],Y refers to the probability of DR,X1 to years of having T2 DM,X2 to systolic blood pressure,X3 to FBG,X4 to Hb A1 c,and X5 to LDL-C.The area under the ROC curve of DR in the model group was 0.884,and the cut-off point was 0.192.The area under the ROC curve was 0.803,the sensitivity was 72.2%,and the specificity was 79.1% in type 2 diabates patients occurred DR in verification group.Conclusion Years of having T2 DM,systolic blood pressure,FBG,Hb A1 c and LDL-C were significantly correlated with DR.DR risk prediction model has certain prediction value for DR.
作者
朱夏媛
吴浩
葛彩英
陈颖
赵新颖
孔慜
高文娟
ZHU Xiayuan;WU Hao;GE Caiying;CHEN Ying;ZHAO Xinying;KONG Min;GAO Wenjuan(Capital Medical University,Beijing 100069,China;Fangzhuang Community Health Service Center,Beijing 100078,China)
出处
《中国全科医学》
CAS
北大核心
2020年第6期712-715,共4页
Chinese General Practice
关键词
糖尿病
2型
糖尿病视网膜病变
危险因素
预测模型
社区卫生中心
Diabetes mellitus,type 2
Diabetic retinopathy
Risk factors
Prediction model
Community health centers
