Construction of a nomogram prediction model for screening of serum markers for lower extremity vasculopathy secondary to type 2 diabetes mellitus

OBJECTIVE: To screen serum markers for secondary lower extremity angiopathy (LEAD) in patients with type 2 diabetes mellitus (T2DM) and construct a nomogram prediction model accordingly. METHODS: The clinical data of 200 T2DM patients admitted to the hospital from December 2022 to October 2024 were retrospectively collected. It was also divided into modeling group (n = 160) and internal validation group (n = 40) in a 4:1 ratio by using the leave-out method. As the external validation group, clinical data from 100 T2DM patients who were admitted to other hospitals within the same time period were also gathered. Combined with previous reports of collecting serum marker data related to LEAD secondary to T2DM, key serum markers were screened using LASSO regression. Moreover, multifactorial analysis helped to clarify independent risk factors, and a nomogram prediction model was built and tested for accuracy. RESULTS: =6.607, 7.962, and 6.585 (p > 0.05). Positive net benefits were obtained by intervening with patients using a nomogram model within the high-risk threshold of 0 to 0.9. CONCLUSION: In this study, eight risk factors associated with LEAD secondary to T2DM are screened by LASSO regression and multifactorial analysis, and a nomogram prediction model is constructed.