2型糖尿病患者糖尿病肾病及非糖尿病性肾脏疾病鉴别诊断预测模型的开发及验证  

Development and validation of a predictive model for the differential diagnosis of diabetic nephropathy and non⁃diabetic renal disease in patients with type 2 diabetes mellitus

作　　者：孙璐璐[1] 尚进[1] 肖静[1] 赵占正[1] Sun Lulu;Shang Jin;Xiao Jing;Zhao Zhanzheng(Department of Nephrology,the First Affiliated Hospital of Zhengzhou University,Zhengzhou 450052,China)

机构地区：[1]郑州大学第一附属医院肾脏内科,郑州450052

出　　处：《中华肾脏病杂志》2020年第11期824-833,共10页Chinese Journal of Nephrology

基　　金：国家自然科学基金(81570690、81873611);河南科技创新团队(17IRTSTHN020);中原科技创新领军人才(194200510006)。

摘　　要：目的旨在建立并验证2型糖尿病患者糖尿病肾病(diabetic nephropathy,DN)及非糖尿病性肾脏疾病(non⁃diabetic renal disease,NDRD)鉴别诊断的预测模型。方法回顾性分析2012年2月至2015年1月在郑州大学第一附属医院进行肾活检的2型糖尿病患者的临床及病理数据,研究人群按7∶3的比例随机分为两个队列:建模队列和验证队列,进行单因素及多因素回归分析筛选预测因子,采用Logistic回归构建预测模型。通过验证队列进行内部验证,计算C统计量,拟合度曲线和Hosmer⁃Lemeshow检验P值评估模型性能,包括区分度、校准度和拟合优度。结果931例2型糖尿病患者中,单纯DN患者478例(51.3%),单纯NDRD患者214例(23.0%),DN合并NDRD(即MIX)患者239例(25.7%)。在NDRD和MIX患者中,膜性肾病均为最常见的病理类型,其次为IgA肾病。最终纳入预测模型的变量有:年龄、糖尿病病程、糖尿病视网膜病变、收缩压、血红蛋白、空腹血糖、糖化血红蛋白、胱抑素C。该模型具有良好的区分度和校准度,建模队列和验证队列的C统计量分别为0.913(95%CI 0.892~0.935)和0.897(95%CI 0.876~0.919),Hosmer⁃Lemeshow检验P=0.934。结论我们建立了一个简单的模型来预测2型糖尿病患者肾穿刺活检病理结果为NDRD及DN合并NDRD的概率,该模型具有较高的准确性。列线图可作为决策支持工具为DN和NDRD的鉴别诊断提供一种简便无创的方法,有助于临床医生评估2型糖尿病肾损害患者肾活检的风险收益比。Objective To develop and validate a predictive model for the differential diagnosis of diabetic nephropathy(DN)and non⁃diabetic renal disease(NDRD)in patients with type 2 diabetes mellitus.Methods A retrospective study with patients with type 2 diabetes who underwent renal biopsy in the First Affiliated Hospital of Zhengzhou University from February 2012 to January 2015 was conducted.The dataset was randomly split into development(70.0%)and validation(30.0%)cohorts.Baseline predictors for model development was selected by using univariable and multivariable logistic regression.The model's performance in the two cohorts,including discrimination and calibration,was evaluated by the C⁃statistic,calibration curve and the P value of the Hosmer⁃Lemeshow test.Results Among the 931 patients with type 2 diabetes,478 cases(51.3%)diagnosed as DN alone,214 cases(23.0%)as NDRD alone and 239 cases(25.7%)as DN plus superimposed NDRD(MIX).Among NDRD and MIX patients,membranous nephropathy was the most common pathological type,followed by IgA nephropathy.The variables selected in the final predictive model were age,duration of diabetes,diabetic retinopathy,systolic blood pressure,hemoglobin,fasting blood glucose,glycosylated hemoglobin,cystatin C.The model performed well with good discrimination and calibration.The C⁃statistics were 0.913(95%CI 0.892-0.935)in the derivation cohort and 0.897(95%CI 0.876-0.919)in the validation cohort.The model had the best P value of 0.934 of the Hosmer⁃Lemeshow test.Conclusions A simple predictive model with high accuracy is constructed for predicting the presence of NDRD and MIX for type 2 diabetic patients.The nomogram can be used as a decision support tool to provide a non⁃invasive method for differential diagnosis of DN and NDRD,which may help clinicians assess the risk⁃benefit ratio of kidney biopsy for type 2 diabetic patients with renal impairment.

关 键 词：糖尿病肾病 糖尿病 2型 诊断 鉴别 非糖尿病性肾脏疾病 预测模型 

分 类 号：R587.2[医药卫生—内分泌] R692.9[医药卫生—内科学]