实用医学杂志2011，Vol.27Issue(21)：3869-3871,3.DOI:10.3969/j.issn.1006-5725.2011.21.016
进展性脑梗死多因素回归分析及判别模型建立
Construction of the model of multivariate regression analysis and discrimination of the risk factors for progressive cerebral infarction
摘要
Abstract
Objective To establish a discriminant model of risk factors for progressive cerebral infarction, and to provide a relatively accurate scientific basis for its early diagnosis. Methods Through logistic regression analysis, key factors for progressive cerebral infarction were selected according to Bayes theory, as well as a discriminant model was established. Results Discriminant model was described as follow: Y1 = -30.381 ± 8.025X7 ± 1.341X8 ± 2.301X21 ± 3.931X31 ± 5.802X32 ± 0.933X33 ± 2.H9X34; Y2= -21.875 ± 6.834X7 ± 2.160X8 ± 3.328X31 ± 3.726X32 ± 2.016X21 ± 0.861X33 ± 1.807X34. Conclusion The discriminant model might be used to contribute to the early diagnosis, early intervention, and timely treatment on progressive cerebral infarction.关键词
脑梗死/多因素回归分析/判别模型Key words
Brain infarction/Multivariate regression analysis/Discriminant model引用本文复制引用
陈莹,孙来芳,龚裕强..进展性脑梗死多因素回归分析及判别模型建立[J].实用医学杂志,2011,27(21):3869-3871,3.
