摘要
目的探究基于临床资料与实验室指标构建2型糖尿病(T2DM)发生糖尿病肾病(DN)的预测模型,并进行预测价值验证,为临床提供相关参考依据。方法选取我院2019年1月至2021年3月T2DM患者267例作为研究对象,根据《糖尿病肾病防治专家共识(2014年版)》中DN诊断标准分为单纯T2DM组(197例)与DN组(70例)。收集两组临床资料、实验室指标,构建T2DM发生DN的Logistic回归模型,评价模型的预测价值,并进行个体值预测验证。结果单因素分析,年龄、性别、BMI、动脉粥样硬化、冠心病、吸烟史、饮酒史、糖尿病家族史、FBG、2hPG、Hb、TG、Scr、BUN不是T2DM发生DN的影响因素(P>0.05);T2DM病程、高血压、HbA1c、TC、HDL-C、LDL-C、SUA是T2DM发生DN的影响因素(P<0.05);Logistic回归分析,T2DM病程、高血压、HbA1c、TC、LDL-C、SUA是T2DM发生DN的独立危险因素,HDL-C是T2DM发生DN的独立保护因素(P<0.05);ROC曲线分析,根据上述独立因素构建Logistic回归模型,该模型预测T2DM发生DN的最佳截断值Log(P)为0.489,AUC为0.830,95%CI为0.779~0.873,灵敏度为61.43%,特异性为89.34%,较各影响因素单独预测价值高。随机抽取2021年4月至2022年1月T2DM患者178例作为验证集,其中发生DN患者42例,未发生DN患者136例,该模型在验证集中预测T2DM发生DN的AUC为0.922,95%CI为0.872~0.957,灵敏度为85.71%,特异性为87.50%。结论基于T2DM病程、高血压、HbA1c、TC、LDL-C、HDL-C、SUA构建T2DM发生DN的预测模型具有可靠预测价值,能作为临床预测DN风险的重要途径。
Objective To construct a predictive model for diabetic nephropathy(DN)in type 2 diabetes mellitus(T2DM)based on clinical data and laboratory indicators,and to validate the predictive value to provide relevant reference for clinical practice.Methods A total of 267 T2DM patients in our hospital from January,2019 to March,2021 were selected as the research objects.According to the"Expert Consensus on the Prevention and Treatment of Diabetic Nephropathy(2014 Edition)",the DN diagnostic criteria were divided into simple T2DM group(197 cases)and DN group(70 cases).We collected two groups of clinical data and laboratory indicators,then constructed a logistic regression model of DN in T2DM,evaluated the predictive value of the model,and validated the individual value prediction.Results Univariate analysis showed that age,gender,BMI,atherosclerosis,coronary heart disease,smoking history,drinking history,family history of diabetes,FBG,2hPG,Hb,TG,Scr,and BUN were not influencing factors of DN in T2DM(P>0.05);The course of T2DM,hypertension,HbA1c,TC,HDL-C,LDL-C,and SUA were identified as influencing factors of DN in T2DM(P<0.05);Logistic regression analysis showed that the course of T2DM,hypertension,HbA1c,TC,LDL-C and SUA were independent risk factors for DN in T2DM,while HDL-C was an independent protective factor for DN in T2DM(P<0.05);ROC curve and logistic regression model were constructed according to the above independent factors to predict the occurrence of DN in T2DM.The best cut-off value of Log(P)was 0.489,while AUC was 0.830,with 95%CI of 0.779-0.873,the sensitivity of 61.43%,and the specificity of 89.34%,which were all higher than the predictive values of each individual influencing factor.A total of 178 T2DM patients from April,2021 to January,2022 were randomly selected as the validation set,including 42 patients with DN and 136 without DN.AUC of the model for predicting DN in T2DM in the validation set was 0.922,with 95%CI of 0.872-0.957,the sensitivity of 85.71%,and the specificity of 87.50%.Conclusion We develop a prediction model for DN in T2DM based on the duration of T2DM,hypertension,HbA1c,TC,LDL-C,HDL-C,and SUA,which has reliable predictive values and can be an important tool to predict DN risk clinically.
作者
邢玉微
刘宽芝
位庚
曹光
孙泽楠
柴雪娇
XING Yuwei;LIU Kuanzhi;WEI Geng;CAO Guang;SUN Zenan;CHAI Xuejiao(Department of Endocrinology,the Second Hospital of Shijiazhuang,Shijiazhuang 050056,China;Department of Endocrinology,the Third Hospital of Hebei Medical University,Shijiazhuang 050051,China)
出处
《标记免疫分析与临床》
CAS
2024年第3期476-481,共6页
Labeled Immunoassays and Clinical Medicine
关键词
2型糖尿病
糖尿病肾病
LOGISTIC回归分析
影响因素
预测价值
Type 2 diabetes mellitus
Diabetic nephropathy
Logistic regression analysis
Influencing factors
Predictive value
