Massey Shavonne L, Shou Haochang, Clancy Robert, DiGiovine Marissa, Fitzgerald Mark P, Fung France W, Farrar John, Abend Nicholas S
Department of Pediatrics (Neurology), Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, U.S.A.
Department of Neurology, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, U.S.A.
J Clin Neurophysiol. 2019 Jan;36(1):1-8. doi: 10.1097/WNP.0000000000000534.
Many neonates undergo electroencephalogram (EEG) monitoring to identify and manage acute symptomatic seizures. Information about brain function contained in the EEG background data may also help predict neurobehavioral outcomes. For EEG background features to be useful as prognostic indicators, the interpretation of these features must be standardized across electroencephalographers. We aimed at determining the interrater and intrarater agreement among electroencephalographers interpreting neonatal EEG background patterns.
Five neonatal electroencephalographers reviewed 5-to-7.5-minute epochs of EEG from full-term neonates who underwent continuous conventional EEG monitoring. The EEG assessment tool used to classify background patterns was based on the American Clinical Neurophysiology Society's guideline for neonatal EEG terminology. Interrater and intrarater agreement were measured using Kappa coefficients.
Interrater agreement was consistently highest for voltage (binary: substantial, kappa = 0.783; categorical: moderate, kappa = 0.562), seizure presence (fair-substantial; kappa = 0.375-0.697), continuity (moderate; kappa = 0.481), burst voltage (moderate; kappa = 0.574), suppressed background presence (moderate-substantial; kappa = 0.493-0.643), delta activity presence (fair-moderate; kappa = 0.369-0.432), theta activity presence (fair-moderate; kappa = 0.347-0.600), presence of graphoelements (fair; kappa = 0.381), and overall impression (binary: moderate, kappa = 0.495; categorical: fair-moderate, kappa = 0.347, 0.465). Agreement was poor or inconsistent for all other patterns. Intrarater agreement was variable, with highest average agreement for voltage (binary: substantial, kappa = 0.75; categorical: substantial, kappa = 0.714) and highest consistent agreement for continuity (moderate-substantial; kappa = 0.43-0.67) and overall impression (moderate-substantial; kappa = 0.42-0.68).
This study demonstrates substantial variability in neonatal EEG background interpretation across electroencephalographers, indicating a need for educational and technological strategies aimed at improving performance.
许多新生儿接受脑电图(EEG)监测以识别和处理急性症状性癫痫发作。EEG背景数据中包含的脑功能信息也可能有助于预测神经行为结果。要使EEG背景特征作为预后指标有用,这些特征的解读必须在脑电图检查人员之间实现标准化。我们旨在确定解读新生儿EEG背景模式的脑电图检查人员之间的评分者间一致性和评分者内一致性。
五名新生儿脑电图检查人员回顾了接受连续常规EEG监测的足月儿5至7.5分钟的EEG片段。用于对背景模式进行分类的EEG评估工具基于美国临床神经生理学会的新生儿EEG术语指南。使用Kappa系数测量评分者间一致性和评分者内一致性。
评分者间一致性在电压方面始终最高(二元:显著,kappa = 0.783;分类:中等,kappa = 0.562)、癫痫发作存在情况(一般至显著;kappa = 0.375 - 0.697)、连续性(中等;kappa = 0.481)、爆发电压(中等;kappa = 0.574)、背景抑制存在情况(中等至显著;kappa = 0.493 - 0.643)、δ活动存在情况(一般至中等;kappa = 0.369 - 0.432)、θ活动存在情况(一般至中等;kappa = 0.347 - 0.600)、图形元素存在情况(一般;kappa = 0.381)以及总体印象(二元:中等,kappa = 0.495;分类:一般至中等,kappa = 0.347, 0.465)。对于所有其他模式,一致性较差或不一致。评分者内一致性各不相同,电压方面平均一致性最高(二元:显著,kappa = 0.75;分类:显著,kappa = 0.714),连续性(中等至显著;kappa = 0.43 - 0.67)和总体印象(中等至显著;kappa = 0.42 - 0.68)的一致性最为稳定。
本研究表明,脑电图检查人员对新生儿EEG背景的解读存在很大差异,这表明需要采取教育和技术策略来提高表现。