Construction and validation of hyperuricemia risk model in diabetic kidney disease patients
Objective To investigate the incidence and risk factors of hyperuricemia (HUA) in patients with diabetic kidney disease (DKD),then construct a nomogram predictive model to guide clinical practice.Method A retrospective summary was conducted on 219 DKD patients diagnosed in our hospital from January 2019 to June 2022 as training set.After admission,they were divided into HUA group (n=102) and non-HUA group (n=117) according to the definition of HUA.Additionally,105 DKD patients from July 2022 to July 2023 were selected as validation set.The general clinical characteristics of patients and average blood biochemical values during the past 3 months were recorded,then univariate and Logistic regression analysis was to analyze the risk factors to HUA in DKD patients,and a nomogram predictive model was established.Result It showed that BMI (OR=1.782),HbA1c (OR=2.601),and hyperlipidemia (OR=1.669) were risk factors to HUA,while eGFR (OR=0.606) was a protective factor.After establishing the nomogram,the consistency indices of training set and validation set were calculated to be 0.854 and 0.802,respectively.The correction curve and ideal curve trends were basically consistent,and the AUC calculated by ROC were 0.867(95％CI=0.802-0.923) and 0.811(95％CI=0.745-0.872),the clinical net benefit value was relatively high,which all indicated that the model had good predictive ability.Conclusion DKD patients usually have a higher prevalence of HUA,with high BMI,high HbA1c,and hyperlipidemia being risk factors,while high eGFR as a protective factor.The construction of nomogram model has good value for guiding early and accurate screen of HUA high-risk groups in clinical practice.
Diabetic kidney diseaseHyperuricemiaNomogramHyperlipidemiaEstimated glomerular filtration rateBody mass indexHemoglobin A1cRisk model
万方数据
维普
