摘要
目的通过构建并验证中老年人群颈动脉斑块的预测模型及对应用价值探讨。方法回顾性收集2017—2019年于上海交通大学医学院附属仁济医院内分泌科门诊完成颈动脉超声检查患者的临床资料,性别不限,年龄≥45岁。共纳入1416例样本,训练集993例,验证集423例。按照7∶3的比例随机分为训练集和验证集,在训练集中比较颈动脉斑块组与非颈动脉斑块组各临床指标差异,并将特征指标变量采用多因素Logistic回归分析确定颈动脉斑块发生的独立危险素,依次构建中老年人群颈动脉斑块发生风险的可视化列线图模型。通过校准曲线和受试者操作特征曲线(receiver operator characteristic curve,ROC曲线)验证模型的区分度、一致性和准确性,最后采用决策曲线分析法确定模型的临床实用性,并通过外部验证进行评估。结果最终本研究纳入1416例患者,有483例(34.11%)有颈动脉斑块。多因素Logistic回归分析结果显示,年龄、收缩压、γ-谷氨酰转肽酶、糖化血红蛋白是颈动脉斑块发生的危险因素,而相较于男性,女性是颈动脉斑块发生的保护因素。依此构建可视化列线图模型,训练集ROC曲线下面积(area under the curve,AUC)为0.75(95%CI:0.72~0.78),验证集ROC曲线的AUC为0.71(95%CI:0.66~0.76)。训练集与验证集校准曲线Hosmer-Lemeshow拟合优度检验显示P值均>0.05(训练集P=0.7501,验证集P=0.9872)。决策曲线结果显示预测模型在训练集和验证集的阈值概率分别为5%~98%和1%~81%。结论基于指标(性别、年龄、收缩压、谷氨酰转肽酶、糖化血红蛋白),成功建立了中老年人群颈动脉斑块发生风险的预测模型,该模型预测效能较好,可用于社区或者农村等偏远地区居民普查,有助于颈动脉斑块的早期识别,进而改善预后。
Objective To construct and validate a predictive model for carotid plaque in middle-aged and elderly populations and to explore its application value.Methods Clinical data were retrospectively collected from patients who underwent carotid ultrasound examinations at the Endocrinology Department of Renji Hospital,Shanghai Jiaotong University School of Medicine,from 2017 to 2019.The patients included were of both genders and aged≥45 years.1416 samples were involved which included 993 for traning and 423 for validation.They were randomly divided into training and validation sets at a 7∶3 ratio.Clinical indicators were compared between the carotid plaque(CP)group and the non-carotid plaque(NCP)group in the training set.Multivariate Logistic regression analysis was used to identify independent risk factors for carotid plaque formation,and a visual nomogram model was constructed to assess the risk of carotid plaque occurrence in the middle-aged and elderly population.The model's discrimination,consistency,and accuracy were verified using calibration curves and receiver operating characteristic(ROC)curves.Finally,the clinical utility of the model was determined using decision curve analysis and further evaluated through external validation.Results A total of 1416 patients were included in the study,with 483 cases(34.11%)having carotid plaques.Multivariate Logistic regression analysis showed that age,systolic blood pressure,gammaglutamyl transferase,and glycated hemoglobin were risk factors for carotid plaque formation,while female gender was a protective factor compared to male gender.Based on these factors,a visual nomogram model was constructed.The area under the ROC curve(AUC)for the training set was 0.75(95%CI:0.72-0.78),and for the validation set,it was 0.71(95%CI:0.66-0.76).The Hosmer-Lemeshow goodness-of-fit test showed P>0.05 for both the training set(P=0.7501)and the validation set(P=0.9872).Decision curve analysis indicated that the threshold probabilities for the training and validation sets were 5%-98%and 1%-81%,respectively.Conclusions A predictive model for carotid plaque occurrence in middle-aged and elderly populations was successfully established based on indicators such as gender,age,systolic blood pressure,gamma-glutamyl transferase,and glycated hemoglobin.The model demonstrated good predictive performance and can be applied in community or remote areas such as rural areas to help early identification of carotid plaques and thus improve the prognosis.
作者
廖宇
黄融
华晨
麻静
Liao Yu;Huang Rong;Hua Chen;Ma Jing(Department of Endocrinology,Renji Hospital,Shanghai Jiaotong University School of Medicine,Shanghai 200127,China;School of Ocean and Civil Engineering,Shanghai Jiaotong University,Shanghai 200240,China)
出处
《中国医学前沿杂志（电子版）》
CSCD
北大核心
2024年第9期56-62,共7页
Chinese Journal of the Frontiers of Medical Science(Electronic Version)
基金
上海市浦东新区卫健委(PW2023-D13)。
关键词
中老年
颈动脉斑块
心脑血管疾病风险
预测模型
Middle-aged and elderly
Carotid plaque
Cardiovascular and cerebrovascular disease risk
Predictive model
