Delayed treatment of diabetic foot ulcer in patients with type 2 diabetes and its prediction model.

Background: Diabetic foot (DF) is a serious complication of type 2 diabetes. This study aimed to investigate the factors associated with DF occurrence and the role of delayed medical care in a cohort of patients with type 2 diabetes.

Aim: To reveal the impact of delayed medical treatment on the development of DF in patients with type 2 diabetes and to establish a predictive model for DF.

Methods: In this retrospective cohort study, 292 patients with type 2 diabetes who underwent examination at our hospital from January 2023 to December 2023 were selected and divided into the DF group ( = 82, DF) and nondiabetic foot group ( = 210, NDF). Differential and correlation analyses of demographic indicators, laboratory parameters, and delayed medical treatment were conducted for the two groups. Logistic regression was applied to determine influencing factors. Receiver operating characteristic (ROC) analysis was performed, and indicators with good predictive value were selected to establish a combined predictive model.

Results: The DF group had significantly higher body mass index (BMI) ( < 0.001), disease duration ( = 0.012), plasma glucose levels ( < 0.001), and HbA1c ( < 0.001) than the NDF group. The NDF group had significantly higher Acute Thrombosis and Myocardial Infarction Health Service System (ATMHSS) scores ( < 0.001) and a significantly lower delayed medical treatment rate (72.38% 13.41%, < 0.001). BMI, duration of diabetes, plasma glucose levels, HbA1c, diabetic peripheral neuropathy, and nephropathy were all positively correlated with DF occurrence. ATMHSS scores were negatively correlated with delayed time to seek medical treatment. The logistic regression model revealed that BMI, duration of diabetes, plasma glucose levels, HbA1c, presence of diabetic peripheral neuropathy and nephropathy, ATMHSS scores, and delayed time to seek medical treatment were influencing factors for DF. ROC analysis indicated that plasma glucose levels, HbA1c, and delayed medical treatment had good predictive value with an area under the curve of 0.933 for the combined predictive model.

Conclusion: Delayed medical treatment significantly affects the probability of DF occurrence in patients with diabetes. Plasma glucose levels, HbA1c levels, and the combined predictive model of delayed medical treatment demonstrate good predictive value.