结合临床数据与复合炎症指标构建预测糖尿病肾脏疾病进展的新模型  

A new model for predicting the progression of diabetic kidney disease constructed by combining clinical data and complex inflammatory indicators

作　　者：李晨子 秦迁[2] 赵琳琳[1] 高梦雅 王守俊[1] Li Chenzi;Qin qian;Zhao Linlin;Gao Mengya;Wang Shoujun(Department of Endocrinology,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内分泌科,郑州450052 [2]郑州大学第一附属医院体检科,郑州450052 [3]郑州大学第一附属医院综合重症监护病区,郑州450052

出　　处：《临床内科杂志》2024年第8期527-530,共4页Journal of Clinical Internal Medicine

基　　金：郑州市协同创新项目(XTCX2023012)。

摘　　要：目的 研究基于临床数据及复合炎症指标构建预测糖尿病肾脏疾病(DKD)进展的新模型。方法 根据24 h尿微量白蛋白水平将239例DKD患者分为DKD早期组(119例)与DKD临床期组(120例)。收集所有患者的一般临床资料及实验室检查结果并分组进行比较。采用单因素、多因素logistic回归分析评估DKD进展的危险因素,并构建预测模型。采用受试者工作特征(ROC)评估新模型精准度,Hosmer-Lemeshow拟合优度检验评估新模型一致性。结果 DKD临床期组患者年龄、糖尿病病程、红细胞沉降率(ESR)、PLT计数、中性粒细胞计数、全身免疫炎症指数(SII)、泛免疫炎症指标(PIV)、PLT/淋巴细胞比值(PLR)均高于DKD早期组,BMI、Hb、淋巴细胞计数均低于DKD早期组(P<0.05)。多因素logistic回归分析结果显示,糖尿病病程、ESR、中性粒细胞计数均为影响DKD进展的独立危险因素(P<0.05)。以上述三项指标得出的预测DKD进展的预测模型:y=-2.677+0.078×ln糖尿病病程(年)+0.045×lnESR(mm/h)+0.251×ln中性粒细胞计数(×10^(9)/L)。ROC曲线分析结果显示,新模型预测DKD进展的曲线下面积(AUC)及特异度均高于SII、PIV及PLR单独预测,敏感度低于SII,高于PIV及PLR。结论 利用糖尿病病程、ESR、中性粒细胞计数构建的新模型预测价值较高,对DKD进展有一定预测价值。复合炎症指标对DKD的进展也存在一定预测价值,可联合预测新模型共同评估DKD进展风险。Objective To construct a new model for predicting the progression of diabetic kidney disease(DKD) based on clinical data and complex inflammatory indicators.Methods A total of 239 patients with DKD were divided into DKD early stage group(119 cases) and DKD clinical stage group(120 cases) according to the quantitative measurement of 24 h urinary microalbumin.General clinical data and laboratory results of all patients were collected and compared in groups.Univariate and multivariate logistic regression analysis were used to assess the risk factors for DKD progression.Construct a new model for prediction.Receiver operating characteristic(ROC) was used to evaluate the model accuracy,and the model calibration was evaluated by Hosmer-Lemeshow goodness of fit test.Results Age,diabetes course,erythrocyte sedimentation rate(ESR),PLT count,neutrophil count,systemic immunoinflammatory index(SII),pan-immunoinflammatory index(PIV) and PLT/lymphocyte ratio(PLR) in DKD clinical stage group were all higher than those in early DKD group,while BMI,Hb and lymphocyte count were all lower than those in early DKD group(P<0.05).Multifactor logistic regression analysis showed that diabetes course,ESR and neutrophils count were independent risk factors for DKD progression(P<0.05).The prediction model for DKD progression consisted of the above three indicators:y=-2.677+0.078×ln diabetes duration(year)+ 0.045×lnESR(mm/h)+0.251×ln neutrophil count(×10^(9)/L).ROC curve analysis results showed that the area under the curve(AUC) and specificity predicted DKD progression by the new model was higher than that predicted by SII,PIV and PLR alone,while sensitivity was lower than SII,and higher than PIV and PLR.Conclusion The new model based on diabetes course,ESR and neutrophil count has high predictive value and can provide certain predictive value for the progression of DKD.The complex inflammatory indicators also have certain predictive value for the progression of DKD,and can be combined with predictive models to jointly assess the progres

关 键 词：红细胞沉降率 中性粒细胞计数 复合炎症指标 糖尿病肾脏疾病 

分 类 号：R856.5[医药卫生—航空、航天与航海医学]