摘要
目的探讨残余胆固醇(RC)联合中性粒细胞/淋巴细胞比值(NLR)预测2型糖尿病肾病(DN)的临床效能。方法选取2020年1月至2022年6月于郑州大学第一附属医院住院治疗的2型糖尿病(T2DM)患者,共755例,收集一般临床资料和实验室指标,采用Spearman秩相关分析RC、NLR与尿微量白蛋白/肌酐比值(UACR)之间的相关性,最小绝对收缩和选择算子(LASSO)回归进行数据筛选、降维,进一步使用多因素logistic回归确立发生DN的独立危险因素,并通过受试者操作特征曲线(ROC曲线)评价RC、NLR及两者联合预测2型糖尿病肾病的临床价值。结果Spearman秩相关结果显示,RC、NLR分别与UACR呈正相关(r=0.362、0.301,P<0.05)。LASSO-logistic回归结果显示,体重指数(BMI)、糖尿病神经病变、糖尿病视网膜病变(DR)、收缩压(SBP)、尿素(Urea)、RC、NLR是DN发生的独立危险因素。ROC曲线显示,RC、NLR及两者联合预测DN的曲线下面积(AUC)分别为0.706、0.669、0.752,敏感度分别为0.693、0.649、0.712,特异度分别为0.646、0.667、0.679;两者联合预测DN的AUC分别高于RC、NLR(Z=2.594、5.115,P<0.05)。结论RC、NLR均可作为2型糖尿病肾病发生的风险预测指标,且两者联合预测时诊断效能更优。
Objective To research the clinical efficacy of remnant cholesterol(RC)combined with neutrophil-to-lymphocyte ratio(NLR)in predicting type 2 diabetic nephropathy(DN).Methods A total of 755 patients with type 2 diabetes mellitus(T2DM)admitted to the First Affiliated Hospital of Zhengzhou University from January 2020 to June 2022 were selected.General clinical data and laboratory indicators were collected and Spearman rank correlation was used to analyze the correlation between RC,NLR and urinary albumin creatinine ratio(UACR).Least absolute shrinkage and selection operator(LASSO)regression was used for data screening and dimensionality reduction.Multivariate logistic regression was further used to establish independent risk factors for DN.The clinical value of RC,NLR and their combination in predicting type 2 diabetic nephropathy was evaluated by receiver operating characteristic(ROC)curve.Results Spearman rank correlation showed that RC and NLR were significantly positively correlated with UACR(r=0.362,0.301,P<0.05).LASSO-logistic regression results showed that body mass index(BMI),diabetic neuropathy,diabetic retinopathy(DR),systolic blood pressure(SBP),Urea,RC and NLR were independent risk factors for DN.ROC curve showed that the area under the curve(AUC)of RC,NLR and their combined prediction of type 2 diabetic nephropathy were 0.706,0.669 and 0.752,the sensitivity was 0.693,0.649 and 0.712,and the specificity was 0.646,0.667 and 0.679,respectively.The area under the curve predicted by the combination of RC and NLR was higher than that of RC and NLR(Z=2.594,5.115,P<0.05).Conclusion Both RC and NLR can be used to predict the risk of type 2 diabetic nephropathy,and their combined prediction is more effective.
作者
付群
贺慧甜
代莹莹
吴文迅
FU Qun;HE Huitian;DAI Yingying;WU Wenxun(Department of Endocrinology,the First Affiliated Hospital of Zhengzhou University,Zhengzhou 450052,China)
出处
《河南医学研究》
CAS
2024年第1期25-30,共6页
Henan Medical Research
