中国临床医学2025，Vol.32Issue(4)：634-641,8.DOI:10.12025/j.issn.1008-6358.2025.20250085
基于β2-微球蛋白和脂蛋白a的脑小血管病MRI总负荷预测模型构建
Construction of a predictive model for cerebral small vessel disease MRI burden based on β2-microglobulin and lipoprotein(a)
摘要
Abstract
Objective To construct a predictive model for cerebral small vessel disease(CSVD)MRI burden based on β2-microglobulin(β2-MG)and lipoprotein(a)[Lp(a)],analyze its predictive value,and validate the model.Methods A total of 138 CSVD patients admitted to Anhui No.2 Provincial People's Hospital from February 2023 to August 2024 were enrolled.Patients were divided into a low-burden group(n=63)and a moderate/severe burden group(n=75)according to the CSVD MRI burden scoring criteria.The related clinical data were compared between the two groups.Binary logistic regression analysis was used to identify independent factors for CSVD moderate/severe MRI burden.A nomogram predictive model was constructed based on these factors and its performance was evaluated.Results The proportions of male patients,as well as those with a history of diabetes or hypertension,were significantly higher in the moderate/severe burden group than those in the low burden group.Additionally,the age of patients in the moderate/severe burden group was significantly older,and the levels of β2-MG,Lp(a),and homocysteine(Hcy)were higher than those in the low burden group(P＜0.01).Binary logistic regression analysis revealed that hypertension,diabetes,β2-MG,and Lp(a)were independent factors for CSVD moderate/severe MRI burden(P＜0.05).The nomogram predictive model based on these four factors had a cut-off value of 0.467 0,with an area under curve(AUC)of 0.838 7(95%CI 0.760 8-0.916 6)in the training set(n=97)and 0.854 1(95%CI 0.742 1-0.966 1)in the internal validation set(n=41).The calibration curve demonstrated good agreement between predicted and observed values.Decision curve analysis(DCA)indicated that the nomogram model had good clinical utility.Conclusions The nomogram model based on β2-MG and Lp(a)has high predictive performance in assessing the risk of CSVD moderate/severe MRI burden,with good discrimination and calibration.关键词
脑小血管病/MRI总负荷/β2-微球蛋白/脂蛋白a/预测模型Key words
cerebral small vessel disease/total MRI burden/β2-microglobulin/lipoprotein(a)/predictive model分类
医药卫生引用本文复制引用
李晓艳,季洪革,王婷婷,李影影,查溪静,李彬,姜丹..基于β2-微球蛋白和脂蛋白a的脑小血管病MRI总负荷预测模型构建[J].中国临床医学,2025,32(4):634-641,8.基金项目
安徽省卫生健康委员会科研计划项目(2018SEYL012).Supported by Scientific Research Project of Health Commission of Anhui Province(2018SEYL012). （2018SEYL012）
