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| Construction and validation of hyperuricemia risk model in diabetic kidney disease patients |
| 1Gu Li,2Xue Song,1Wang Ping |
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Abstract 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.
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