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基于统计模型的脑出血部位与患者昏迷症状关联分析 被引量:2

Correlation analysis of coma symptoms in patients with cerebral hemorrhage based on statistical model
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摘要 目的为探明高血压性脑出血患者昏迷与脑出血部位的相关性。方法对396例临床病例的CT图像数据采集及处理,形成研究数据。分别建立高血压性脑出血4种常见部位出血量以及出血是否破入脑室,与临床昏迷的单因子线性拟合方程,计算单因素相关系数;建立多因素线性拟合方程,并与单因子拟合结果比较。结果出血破入脑室与昏迷的线性相关系数最高,为0. 84,而其它4种部位出血量大小与临床昏迷的相关系数明显低于此水平;在全部396例中,单一部位出血但未破入脑室的情况下,引起临床昏迷的比例仅为3. 33%。结论高血压性脑出血破入脑室与临床昏迷具有相关性,而且预后差,该结论对探寻高血压性脑出血患者昏迷的病理指明了新方向。 Objective To investigate the correlation between patients’ coma and the position of hypertensive cerebral hemorrhage. Methods A retrospective analysis of 396 patients’ cases were collected and the original CT imaging data were analyzed and dealt to form the original research data. The bleeding amount of 4 different positions and whether ventricle hemorrhage existed were taken into concern as 5 factors, and then the a linear equation between each factor and the clinical exanimation were established and correlation coefficient was calculated, respectively. Multivariate equation was also built for comparison. Results Correlation coefficient between ventricle hemorrhage and patients’ coma was the highest, 0.84, far more than the other 4 factors. Only 3.33% cerebral hemorrhage at single position without ventricle hemorrhage leaded to patients’ coma. Conclusion Ventricle hemorrhage is the main factor of the patients’ coma, and this Conclusion indicates a new direction to explore the pathology of coma in patients with cerebral hemorrhage.
作者 巩宁 秦立峰 段海峰 范小璇 米伟 GONG Ning;QIN Li-feng;DUAN Hai-feng;FAN Xiao-xuan;MI Wei(Department of Radiology,Yangling Hospital,Yangling 712100;College of Mechanical and ElectricalEngineering,Northwest A&F University,Yangling 712100;Affiliated Hospital of Shaanxi University of Chinese Medicine,Xianyang 712000;Jingyang County Hospital,Xianyang 713700,China)
出处 《延安大学学报(医学科学版)》 2018年第3期62-65,共4页 Journal of Yan'an University:Medical Science Edition
基金 陕西省中医药科研课题(15-LC009)
关键词 脑出血 高血压性脑出血 脑室 昏迷 统计模型 Cerebral hemorrhage Hypertensive intracerebral hemorrhage Cerebral ventricular Coma Statistical model
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