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[Nomogram analysis of risk factors for diabetic neuropathy in primary type 2 diabetic mellitus patients in Zhejiang
1Department of Endocrinology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310016, China.
Abstract:
Objective: To investigate the risk factors of diabetic nephropathy (DN) in primary type 2 diabetes mellitus (T2DM) patients and to quantitatively analyze the risk of DN by nomogram modeling. Methods: A total of 1 588 primary T2DM patients from 17 townships and streets in Zhejiang Province were enrolled from June 2018 to August 2018 in this cross-sectional study, with an average age of (56.8±10.1) years (50.06% male) and a mean disease duration of 9 years. The clinical data, biochemical test results, and fundus photographs of all T2DM patients were collected, and logistic regression analysis was used to screen the risk factors of DN. Then, a nomogram model was used to quantitatively analyze the risk of DN. Results: DN occurred in 27.71% (440/1 588 cases) primary type 2 diabetes patients. Hemoglobin A1c (HbA1c) (OR=1.159, 95%CI 1.039-1.292), systolic blood pressure (OR=1.041, 95%CI 1.031-1.051), serum creatinine (Scr) (OR=1.011, 95%CI 1.004-1.017), serum globulin (GLOB) (OR=1.072, 95%CI 1.039-1.105), diabetic retinopathy (DR) (OR=1.463, 95%CI 1.073-1.996), education level of more than junior high school (OR=2.018, 95%CI 1.466-2.777), and moderate-intensity exercise (OR=0.751, 95%CI 0.586-0.961) were influencing factors of DN. Nomogram model analysis showed that the total score of each factor of DN ranged from 64-138 points, and the corresponding risk rate ranged from 0.1-0.9. The nomogram model also predicted a C-index value of 0.753 (95%CI 0.726-0.781) and an area under the receiver operating characteristic curve of DN of 0.753. Internal verification of the C-index reached 0.738. The model displayed medium predictive power and could be applied in clinical practice. Conclusions: HbA1c, systolic blood pressure, Scr, GLOB, DR, and more than a junior high school education are independent risk factors of DN. Nomogram modeling can more intuitively evaluate the risk of DN in primary T2DM patients.
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