湖南中医药大学学报2017，Vol.37Issue(11)：1238-1242,5.DOI:10.3969/j.issn.1674-070X.2017.11.017
应用logistic回归模型预测急性缺血性脑卒中发生概率的病例对照研究
A Case Control Study of Predicting Probability for Acute Ischemic Stroke Applying the Logistic Regression Model
摘要
Abstract
Objective To analyze the influencing factors of ischemic stroke, and establish the prediction model of morbidity, so that can provide evidence for ischemic stroke prevention before disease onset. Methods A case-control study was adopted for statistical analysis. Then the conditional logistic regression method was used to build up predictive model and ROC method was utilized to evaluate predictive effect of this model. Results The main risk factors of ischemic stroke included N-terminal brain natriuretic peptide in hyperacute phase (NT-proBNP), astrocyte specific protein (S100B), high sensitive C re-active protein (Hs-CRP), lysophosphatide acid (LPA) were higher than the control group, while matrix metalloproteinase-9 (MMP-9) had no significant difference. Eyeground arteriosclerosis and LPA were selected into the logistic regression model, and the ROC area under the curve reaches 0.9761. Conclusion NT-proBNP, S100B, Hs-CRP, LPA could predict the morbidity of diseases preferably, and the logistics regression model including variables of LPA and eyeground arteriosclero-sis can predict probability for acute ischemic stroke accurately.关键词
急性缺血性卒中/logistic回归模型/眼底动脉硬化/溶血磷脂酸Key words
acute ischemic stroke/logistic regression model/eyeground arteriosclerosis/lysophosphatidic acid分类
医药卫生引用本文复制引用
王若君,陈建华,张军,黄燕,王永炎..应用logistic回归模型预测急性缺血性脑卒中发生概率的病例对照研究[J].湖南中医药大学学报,2017,37(11):1238-1242,5.基金项目
第43期中国博士后科学基金会基金资助项目课题"急性缺血性卒中急性期证候演变规律与细胞因子相关性研究"( 20080430860) （ 20080430860）
"十一五"国家科技支撑计划重大项目"缺血性卒中综合防治方案和疗效评价的示范研究"课题(2006BA104A02). （2006BA104A02）
