当前位置: 首页 > 详情页

Predicting the non-survival outcome of large hemispheric infarction patients via quantitative electroencephalography: Superiority to visual electroencephalography and the Glasgow Coma Scale

| 导出 | |

文献详情

资源类型:
WOS体系:

收录情况: ◇ SCIE

机构: [1]Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
出处:
ISSN:

关键词: EEG grading GCS Large hemispheric infarction Prognosis Quantitative EEG

摘要:
Background: Quantitative electroencephalography (QEEG) data are useful to predict outcomes of cerebral infarction patients. This study was performed to establish the value of QEEG in the prediction of outcomes in patients with large hemispheric infarction (LHI). Methods: A prognostic blinded cohort study was conducted on patients diagnosed with LHI in our neurocritical care unit. The electroencephalography (EEG) was recorded at the bedside within 3 days of LHI onset. Each EEG expert scored the raw EEG, and QEEG parameters including the absolute power, (delta + theta)/ (alpha + beta) ratio and brain symmetry index were obtained afterwards. Baseline data including Glasgow Coma Scale (GCS) was recorded at the meantime. Outcomes included survival or non-survival at the time of discharge and 6 months after the onset of LHI. Results: A total of 50 patients entered into the final analysis. There were no differences in baseline data or visual EEG grades between survival and non-survival groups. QEEG analysis showed that the absolute theta power of all of the electrodes and the contralateral electrodes was significantly higher in the non-survival group than in the survival group at discharge. Multivariable logistic regression analysis demonstrated that theta power of the contralateral electrodes was an independent predictor of death at discharge and at 6 months. Compared to the GCS and EEG grading, the QEEG index exhibited higher accuracy in predicting non-survival outcomes. Conclusions: Among QEEG indices, theta power is valuable in predicting non-survival outcome in participants and is superior to visual EEG and GCS. © 2019

基金:
语种:
被引次数:
WOS:
PubmedID:
中科院(CAS)分区:
出版当年[2018]版:
大类 | 4 区 医学
小类 | 4 区 神经科学
最新[2025]版:
大类 | 4 区 医学
小类 | 4 区 神经科学
JCR分区:
出版当年[2017]版:
Q3 NEUROSCIENCES
最新[2023]版:
Q3 NEUROSCIENCES

影响因子: 最新[2023版] 最新五年平均 出版当年[2017版] 出版当年五年平均 出版前一年[2016版] 出版后一年[2018版]

第一作者:
第一作者机构: [1]Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
通讯作者:
通讯机构: [1]Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China [*1]Department of Neurology Xuanwu Hospital, Capital Medical University, No. 45 Changchun Street, Xicheng District, Beijing, 100053, China.
推荐引用方式(GB/T 7714):
APA:
MLA:

资源点击量:16991 今日访问量:1 总访问量:905 更新日期:2025-04-01 建议使用谷歌、火狐浏览器 常见问题

版权所有©2020 首都医科大学宣武医院 技术支持:重庆聚合科技有限公司 地址:北京市西城区长椿街45号宣武医院