Construction and Validation of a Predictive Nomogram Model for Patients with Type 2 Diabetes Complicated by Diabetic Foot Ulcers

Abstract

Objective: To investigate the risk factors for diabetic foot ulcers (DFU) in patients with type 2 diabetes (T2DM), to create a nomogram prediction model, and to further validate the nomogram model. 500 T2DM patients treated at Shanghai Integrated Traditional Chinese and Western Medicine Hospital were retrospectively analyzed from April 2023 to November 2023. Patients were categorized into groups based on the presence of DFU (n = 64) and T2DM (n = 436). Clinical data were analyzed, and relevant parameters were assessed using a receiver operating curve (ROC) analysis. A risk prediction model was created using the R language software 4.0 “rms” and validated using calibration and decision curves. Age, diabetes duration, coronary heart disease, cerebrovascular disease, diabetic nephropathy, HbA1c, and fasting blood glucose were significantly higher in the DFU group (OR = 1.598,1.444,1.101,1.210,1.414,2.132,1.935，all P＜0.001). Gender, family history of diabetes, hypertension, peripheral neuropathy, drug regimen, and lipid levels showed no significant differences (P > 0.05). Logistic regression analysis identified age, diabetes duration, athlete's foot infection, HbA1c, and fasting blood glucose as independent risk factors for DFU in T2DM. The nomogram model yielded a C-index of 0.822 (95% CI: 0.813–0.882), indicating a net clinical benefit. The constructed nomogram prediction model based on age, diabetes duration, athlete's foot infection, HbA1c, and fasting blood glucose provides a simple assessment method for DFU in T2DM patients. Further validation of this model is warranted.