基于临床基线特征与颈动脉超声参数构建脑卒中高危人群颈动脉易损斑块模型  

Constructing a Nomogram model of vulnerable carotid plaques in patients at high risk of stroke based on clinical baseline characteristics and carotid ultrasound parameters

作　　者：秦杰[1] 李玉娟 王苾莉 赖泽飞 马悦茗 Qin Jie;Li Yujuan;Wang Bii;Lai Zefei;Ma Yueming(First People’s Hospital of Fuzhou,Fuzhou 344000,Jiangxi Province,China;Jiangxi Combined Traditional Chinese and Western Medicine Hospital,Nanchang 330000,Jiangxi Province,China)

机构地区：[1]江西省抚州市第一人民医院,江西省抚州市344000 [2]江西省中西医结合医院,江西省南昌市330000

出　　处：《中国组织工程研究》2025年第12期2444-2449,共6页Chinese Journal of Tissue Engineering Research

基　　金：江西省中医药管理局科技计划项目(2022B223),项目负责人:赖泽飞;江西省卫生健康委科技计划项目(202311244),项目负责人:马悦茗。

摘　　要：背景:研究表明,颈动脉斑块的易损性和弹性与斑块内新生血管的存在及形成程度有关。超声作为筛查和评价颈动脉易损斑块的首选检查手段,具有无创、操作便捷、可重复性高和无辐射等的特点。目的:基于临床基线特征与颈动脉超声参数,探讨脑卒中高危人群颈动脉易损斑块的影响因素,基于独立危险因素构建并验证风险列线图(Nomogram)预测模型。方法:回顾性选取2021年11月到2023年11月于抚州市第一人民医院行脑卒中筛查确定为脑卒中高危人群的180例患者作为研究对象,将180例患者按7∶3比例分为建模集(n=126)和验证集(n=54),根据颈动脉超声检查结果将建模集研究对象分为易损斑块组(n=54)和非易损斑块组(n=72)。通过多因素Logistic回归得出独立危险因素,构建Nomogram模型,并使用R语言绘制决策曲线以评估模型的临床效益。采用受试者工作特征曲线和校准曲线检验模型的预测效能,同时分析验证集的病例数据进行外部验证。结果与结论:①多因素Logistic回归结果显示,年龄、脑卒中家族史、颈动脉斑块最大厚度值、颈动脉斑块数量、尿微量白蛋白和尿微量白蛋白/肌酐均与脑卒中高危人群颈动脉易损斑块有关(P<0.05)。②构建的Nomogram模型受试者工作特征曲线下面积为0.917,灵敏度和特异度分别为79.6%和91.7%;决策曲线结果显示,该模型的潜在临床获益可观,可用性较高;校准曲线结果提示,模型具备较好的预测准确性;验证集结果显示,模型的外部预测性能良好。③结果说明,脑卒中高危人群颈动脉易损斑块受年龄、脑卒中家族史、颈动脉斑块最大厚度值等因素影响,基于各独立危险因素构建的风险Nomogram预测模型的预测性能良好,可为临床上治疗此类高危人群提供有力的参考依据。BACKGROUND:Studies have shown that the vulnerability and elasticity of carotid plaques are related to the presence and degree of neovascularization within the plaque.Ultrasound,as the preferred measure to screen and evaluate vulnerable carotid plaques,is non-invasive,easy to perform,highly reproducible and radiation-free.OBJECTIVE:To investigate the influencing factors of vulnerable carotid plaque in the high-risk stroke population based on clinical baseline characteristics and carotid ultrasound parameters,and to develop a Nomogram prediction model based on independent risk factors.METHODS:A total of 180 patients who were identified to be at high risk of stroke by stroke screening at Fuzhou First People’s Hospital from November 2021 to November 2023 were retrospectively selected as the study objects,and the patients were divided into a modeling set(n=126)and a validation set(n=54)at a ratio of 7:3.According to the results of carotid artery ultrasound,the subjects in the modeling set were divided into a vulnerable plaque group(n=54)and a non-vulnerable plaque group(n=72).Independent risk factors were obtained by multi-factor Logistic regression,and a Nomogram model was constructed.Decision curves were drawn using R language to evaluate the clinical benefit of the model.The predictive efficacy of the model was tested by receiver operating characteristic curve and calibration curve,and the case data of the validation set were analyzed for external validation.RESULTS AND CONCLUSION:Multivariate Logistic regression results showed that age,family history of stroke,maximum carotid plaque thickness,carotid plaque quantity,urine microalbumin,urine microalbumin/creatinine ratio were associated with vulnerable carotid plaques in patients at high risk of stroke(P<0.05).The area under curve of the established Nomogram model was 0.917,and the sensitivity and specificity were 79.6%and 91.7%,respectively.The results of decision curve showed that the potential clinical benefit of this model was considerable and its usability w

关 键 词：临床基线特征 颈动脉超声参数 脑卒中高危人群 颈动脉斑块 NOMOGRAM 

分 类 号：R459.9[医药卫生—治疗学] R318[医药卫生—临床医学] R496