Journal of Jilin University(Medicine Edition) ›› 2026, Vol. 52 ›› Issue (3): 806-812.doi: 10.13481/j.1671-587X.20260322

• Research in clinical medicine • Previous Articles    

Analysis on influencing factors in type 2 diabetes mellitus patients complicated with lower limb atherosclerosis and construction of nomogram model

Jing YU1,Yinzhuo HUANG,Zhongwei ZHOU2,Yuxin XIE1,Qian MAO1()   

  1. 1.Department of Endocrinology,Affiliated Hospital,Beihua University,Jilin 132012,China
    2.Department of General Surgery,Affilicated Hospital,Beihua University,Jilin 132012,China
  • Received:2025-10-13 Accepted:2025-11-23 Online:2026-05-28 Published:2026-06-08
  • Contact: Qian MAO E-mail:maoqian@beihua.edu.cn

Abstract:

Objective To discuss the risk factors in the type 2 diabetes mellitus (T2DM) patients complicated with low extremity atherosclerosis (LEAD), and to establish a nomogram prediction model, so as to provide clinical basis for early identification of high-risk populations and formulation of intervention strategies. Methods The clinical data of 269 patients with T2DM were collected. The patients were divided into LEAD group (n=197) and non-LEAD group (n=72) according to whether they had concurrent LEAD. Univariate and multivariate Logistic regression analyses were used to analyze the risk factors of T2DM patients complicated with LEAD; the nomogram was used to construct a risk prediction model; the Bootstrap method (B=1 000) was used for internal validation; the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) were used to comprehensively evaluate the predictive performance of the model. Results The univariate analysis results showed that compared with non-LEAD group, the age, disease duration, fasting plasma glucose (FBG), body mass index(BMI), triglyceride (TG), smoking history, and history of hypertension in the patients in LEAD group had statistically significant differences (P<0.05). The multivariate Logistic regression analysis results showed that patients’ age [odds ratio (OR)=1.082, 95% confidence interval (CI): 1.039-1.127, P<0.001], BMI(OR=1.287, 95%CI: 1.154-1.436, P<0.001), and FBG (OR=1.159, 95%CI: 1.043-1.288, P=0.006) were the independent risk factors for T2DM complicated with LEAD. The Bootstrap internal consistency index (C-index) was 0.841 (95%CI: 0.793-0.890), indicating that the model had good discriminative performance. The calibration curve analysis results showed that the Brier score was 0.138, and the predicted probability was highly consistent with the actual observed probability, indicating good calibration of the model. The DCA standardized net benefit value ranged from 0.2 to 0.8, indicating that the model had a significant net benefit advantage. Conclusion High BMI level is an important influencing factor for the T2DM patients complicated with LEAD. The constructed nomogram risk model based on the risk factors has good predictive performance.

Key words: Body mass index, Type 2 diabetes mellitus, Lower extremity atherosclerosis, Prediction model, Risk factors

CLC Number: 

  • R587.1