A non-laboratory-based risk score for predicting diabetic kidney disease in Chinese patients with type 2 diabetes

Aim To construct a simple screening tool for predicting diabetic kidney disease in Chinese patients with type 2 diabetes. Materials and Methods In the development cohort, the clinical and procedural characteristics of the 4,795 patients were considered as candidate univariate predictors of diabetic kidney disease. The β-coefficients derived from a multiple logistic regression model predicting the presence of DKD were used to calculate the risk score. The performance of the risk score was validated in a cross-sectional and a prospective cohort population. Results The risk score included sex, body mass index, systolic blood pressure, and duration of diabetes. The total point ranged from 0 to 39. In the development cohort, compared with participants with risk score < 10, those with risk score between 10 to 20, 21 to 30, and > 30 had ORs of 3.21, 7.92 and 17.55 for developing diabetic kidney disease, respectively. In the prospective cohort, 60.9% patients with risk score over 30 were expected to develop DKD at 72 months of follow-up. Conclusions Sex, body mass index, systolic blood pressure, and duration of diabetes were independent predictors of diabetic kidney disease, and the derived risk equation was a simple screening tool for screening diabetic kidney disease in Chinese patients with type 2 diabetes.