影像科学与光化学2025，Vol.43Issue(6)：20-26,7.DOI:10.7517/issn.1674-0475.2025.06.03
基于超声构建糖尿病患者颈动脉粥样硬化风险预测模型
Establishment of a Risk Prediction Model for Carotid Atherosclerosis in Diabetic Patients Based on Ultrasound
摘要
Abstract
Objective:To investigate the risk factors of carotid atherosclerosis(CAS)in diabetic patients and develop a predictive model for CAS occurrence using ultrasound.Methods:A total of 194 patients with type 2 diabetes mellitus(T2DM)admitted to our hospital from August 2022 to April 2024 were recruited for carotid artery ultrasonography and questionnaire surveys.Patients were divided into CAS and non-CAS groups based on ultrasound results.Basic demographics,physical examination data,and biochemical indicators were compared between groups.Binary Logistic regression analysis was performed to identify risk factors for CAS.A predictive model was constructed using the rms package in R3.6.3 software.The area under the ROC curve(AUC)and calibration curve were used to evaluate the model's predictive performance,and the clinical benefit was analyzed by a decision curve.Results:Of the 194 T2DM patients,91(46.91%)had CAS.The CAS group had significantly higher proportions of patients aged over 65,with OSAS history,and higher systolic blood pressure,FBG,GHb,LDL-C,Hcy,and serum uric acid levels compared to the non-CAS group(P<0.05).Logistic regression analysis identified age>65 years,high systolic blood pressure,high GHb,high LDL-C,high Hcy,and high serum uric acid as independent risk factors for CAS.The predictive model showed an AUC of 0.849(95%CI:0.795～0.902),and the calibration curve fitted well,with a higher net benefit rate when the threshold probability ranged from 3%to 89%.Conclusion:The predictive model based on age,systolic blood pressure,GHb,LDL-C,Hcy,and blood uric acid levels can effectively predict the risk of CAS in T2DM patients,facilitating early identification of high-risk individuals and targeted interventions.关键词
糖尿病/颈动脉粥样硬化/危险因素/预测模型Key words
diabetes mellitus/carotid atherosclerosis/risk factors/predictive model分类
医药卫生引用本文复制引用
谢丽,冯佩云,刘彦,谢萍,陈静,蔡晓丽..基于超声构建糖尿病患者颈动脉粥样硬化风险预测模型[J].影像科学与光化学,2025,43(6):20-26,7.基金项目
四川省西部精神医学协会石药LEADING科研基金项目(WL2022001) （WL2022001）
江苏省苏北人民医院院级护理研究专项项目(SBHL23033). （SBHL23033）
