脑电图对缺氧缺血性脑损伤后神经系统结果的预测:系统综述和荟萃分析。

Xina Ding, Zhixiao Shen
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引用次数: 0

摘要

背景预测缺氧缺血性脑损伤(HIBI)后的神经系统结果是困难的。客观的脑电图(EEG)可以识别缺氧性脑损伤后的急性和亚急性脑异常,并预测HIBI的恢复。我们检查了脑电对HIBI后神经系统结果的预测能力。方法在Medline、Embase、Cochrane和Central数据库中进行了符合PRISMA的搜索,直到2023年1月。从相关角度和回顾性队列研究中选择脑电预测HIBI患者的神经系统结果。RevMan进行了荟萃分析,而QDAS2评估了研究质量。后果11项对3761名HIBI患者的研究符合纳入和排除标准。我们在适当的情况下,使用随机效应双变量和单变量荟萃分析,汇总了EEG模式的敏感性和特异性的研究水平估计。阳性指标和解剖区域异质性影响预后准确性。漏斗图分析了出版偏差。在纳入的研究中,显著的异质性大于80%,P P 结论脑电图可以以良好的预后准确性预测HIBI的结果,但需要更标准的交叉研究协议和脑电图模式的描述来更好地评估其对HIBI患者的预后用途。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Electroencephalography Prediction of Neurological Outcomes After Hypoxic-Ischemic Brain Injury: A Systematic Review and Meta-Analysis.

Background. Predicting neurological outcomes after hypoxic-ischemic brain injury (HIBI) is difficult. Objective. Electroencephalography (EEG) can identify acute and subacute brain abnormalities after hypoxic brain injury and predict HIBI recovery. We examined EEG's ability to predict neurologic outcomes following HIBI. Method. A PRISMA-compliant search was conducted in the Medline, Embase, Cochrane, and Central databases until January 2023. EEG-predicted neurological outcomes in HIBI patients were selected from relevant perspective and retrospective cohort studies. RevMan did meta-analysis, while QDAS2 assessed research quality. Results. Eleven studies with 3761 HIBI patients met the inclusion and exclusion criteria. We aggregated study-level estimates of sensitivity and specificity for EEG patterns determined a priori using random effect bivariate and univariate meta-analysis when appropriate. Positive indicators and anatomical area heterogeneity impacted prognosis accuracy. Funnel plots analyzed publication bias. Significant heterogeneity of greater than 80% was among the included studies with P < 0.001. The area under the curve was 0.94, the threshold effect was P < 0.001, and the sensitivity and specificity, with 95% confidence intervals, were 0.91 (0.84-0.99) and 0.86 (0.75-0.97). EEG detects status epilepticus and burst suppression with good sensitivity, specificity, and little probability of false-negative impairment result attribution. Study quality varied by domain, but patient flow and timing were well conducted in all. Conclusion. EEG can predict the outcome of HIBI with good prognostic accuracy, but more standardized cross-study protocols and descriptions of EEG patterns are needed to better evaluate its prognostic use for patients with HIBI.

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