Journal of Jilin University(Medicine Edition) ›› 2025, Vol. 51 ›› Issue (4): 1028-1038.doi: 10.13481/j.1671-587X.20250419

• Research in clinical medicine • Previous Articles    

Analysis on influencing factors for occurrence of angina pectoris in diabetic mellitus patients and its Bayesian network risk prediction

Shuang LI,Jiayu GE,Xianzhu CONG,Aimin WANG,Yujia KONG,Fuyan SHI(),Suzhen WANG()   

  1. Department of Health Statistics,School of Public Health,Shandong Second Medical University,Weifang 261053,China
  • Received:2024-08-29 Accepted:2024-10-31 Online:2025-07-28 Published:2025-08-25
  • Contact: Fuyan SHI,Suzhen WANG E-mail:shifuyan@sdsmu.edu.cn;wangsz@sdsmu.edu.cn

Abstract:

Objective To discuss the influencing factors of angina pectoris in the patients with diabetes mellitus (DM), to construct a Bayesian network model to explore the network relationships among the influencing factors, and to predict the risk of angina pectoris in the patients with DM. Methods Based on the UK Biobank(UKB) database, the Logistic regression aralysis model was used to screen the influencing factors of angina pectoris in the patients with DM. The taboo search algorithm was used for structure learning, and the Bayesian parameter estimation method was used for parameter learning to construct the Bayesian network model. Results A total of 22 712 DM patients were included. The influencing factors of angina pectoris in the patients with DM included 14 variables: gender, age, body mass index (BMI), triglycerides (TG), total cholesterol (TC), glycated hemoglobin (HbA1c), hypertension, maternal smoking around delivery, smoking status, alcohol consumption, regular exercise, insomnia, sleep duration, and childhood relative body size (P<0.05). A Bayesian network model was constructed with 15 nodes and 22 directed edges. Among them, age, HbA1c, hypertension, regular exercise, BMI, and sleep duration were directly associated with the occurrence of angina pectoris in the patients with DM, while gender, smoking status, alcohol consumption, TC, TG, insomnia, childhood relative body size, and maternal smoking around delivery were indirectly associated with the occurrence of angina pectoris in the patients with DM. Conclusion Age, HbA1c, hypertension, regular exercise, BMI, and sleep duration are direct influencing factors of angina pectoris in the patients with DM. Controlling HbA1c, blood pressure, and BMI levels, engaging in regular exercise, and maintaining appropriate sleep duration are beneficial for reducing the risk of angina pectoris in the patients with DM.

Key words: Diabetes mellitus, Angina pectoris, Bayesian network, Risk prediction, Taboo search algorithm

CLC Number: 

  • R587.1