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Sources of interrater variability and prognostic value of standardized EEG features in post-anoxic coma after resuscitated cardiac arrest

机译:复苏的心脏骤停后缺氧性昏迷中跨度变异性和标准化脑电图特征的预后价值来源

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ObjectivesTo assess interrater variability and prognostic value of simple EEG features based on the recent American Clinical Neurophysiology Society (ACNS) classification in post cardiac arrest comatose patients.MethodsAll patients admitted for a resuscitated cardiac arrest in a university hospital were prospectively included in the study. EEG interpretation was made by 3 independent neurophysiologists (2 senior and 1 junior) blind to the outcome. Kappa score and prognostic performances were estimated for each EEG pattern and discrepancies were analyzed.Results122 cardiac arrest patients were admitted of whom 48 went through a full neurologic evaluation. Eighty-one percent had an unfavorable outcome. Burst suppression, paroxystic seizure activity, and non-reactive EEG were strongly associated with an unfavorable evolution. Kappa score between the senior neurophysiologists was excellent or substantial while it was only fair or slight between the junior and senior neurophysiologists. Reactivity, discontinuity and electrographic seizure were patterns particularly subject to discrepancy.ConclusionsBedside EEG is an excellent tool for predicting outcome of post-anoxic coma through simple EEG features. However, the interrater variability emphasizes the need to be well trained for the standardized methods of evaluating EEG parameters.SignificanceA second look at complex patterns seems mandatory. The development of automated tools could help to improve the reliability of EEG interpretation.
机译:目的根据最近的美国临床神经生理学协会(ACNS)分类来评估心脏骤停后昏迷患者的简单脑电图特征的间期变异性和预后价值。脑电图的解释是由3名独立于结果的独立神经生理学家(2名高级和1名初级)进行的。评估每种脑电图的Kappa评分和预后表现,并分析差异。结果纳入122例心脏骤停患者,其中48例经过了全面的神经系统评估。百分之八十一的结果不理想。爆发抑制,阵发性癫痫发作活动和非反应性脑电图与不良的进化密切相关。高级神经生理学家之间的Kappa得分极好或很高,而初级和高级神经生理学家之间的Kappa得分仅中等或中等。反应性,间断性和电图发作是特别容易出现差异的模式。结论床旁脑电图是通过简单的脑电图特征预测缺氧性昏迷预后的极佳工具。但是,界面变异性强调需要对评估脑电参数的标准化方法进行充分的培训。意义复习复杂模式似乎是强制性的。自动化工具的开发可以帮助提高EEG解释的可靠性。

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