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脑电图技术员与神经生理学家之间的观察者间一致性的前瞻性评估。

Prospective evaluation of interrater agreement between EEG technologists and neurophysiologists.

机构信息

Epilepsy Center Frankfurt Rhine-Main and Department of Neurology, Center of Neurology and Neurosurgery, Goethe-University Frankfurt, Schleusenweg 2-16 (Haus 95), 60528, Frankfurt am Main, Germany.

LOEWE Center for Personalized Translational Epilepsy Research (CePTER), Goethe-University Frankfurt, Schleusenweg 2-16, 60528, Frankfurt am Main, Germany.

出版信息

Sci Rep. 2021 Jun 28;11(1):13406. doi: 10.1038/s41598-021-92827-3.

Abstract

We aim to prospectively investigate, in a large and heterogeneous population, the electroencephalogram (EEG)-reading performances of EEG technologists. A total of 8 EEG technologists and 5 certified neurophysiologists independently analyzed 20-min EEG recordings. Interrater agreement (IRA) for predefined EEG pattern identification between EEG technologists and neurophysiologits was assessed using percentage of agreement (PA) and Gwet-AC1. Among 1528 EEG recordings, the PA [95% confidence interval] and interrater agreement (IRA, AC1) values were as follows: status epilepticus (SE) and seizures, 97% [96-98%], AC1 kappa = 0.97; interictal epileptiform discharges, 78% [76-80%], AC1 = 0.63; and conclusion dichotomized as "normal" versus "pathological", 83.6% [82-86%], AC1 = 0.71. EEG technologists identified SE and seizures with 99% [98-99%] negative predictive value, whereas the positive predictive values (PPVs) were 48% [34-62%] and 35% [20-53%], respectively. The PPV for normal EEGs was 72% [68-76%]. SE and seizure detection were impaired in poorly cooperating patients (SE and seizures; p < 0.001), intubated and older patients (SE; p < 0.001), and confirmed epilepsy patients (seizures; p = 0.004). EEG technologists identified ictal features with few false negatives but high false positives, and identified normal EEGs with good PPV. The absence of ictal features reported by EEG technologists can be reassuring; however, EEG traces should be reviewed by neurophysiologists before taking action.

摘要

我们旨在前瞻性地研究,在一个大型和异质的人群中,脑电图(EEG)技术员的 EEG 阅读表现。共有 8 名脑电图技术员和 5 名认证神经生理学家独立分析了 20 分钟的脑电图记录。脑电图技术员和神经生理学家之间预定义 EEG 模式识别的组内一致性(IRA)使用一致性百分比(PA)和 Gwet-AC1 进行评估。在 1528 份脑电图记录中,PA[95%置信区间]和组内一致性(IRA、AC1)值如下:癫痫持续状态(SE)和癫痫发作,97%[96-98%],AC1kappa=0.97;间发性癫痫样放电,78%[76-80%],AC1=0.63;以及结论分为“正常”与“病理性”,83.6%[82-86%],AC1=0.71。脑电图技术员识别 SE 和癫痫发作的阴性预测值为 99%[98-99%],而阳性预测值(PPV)分别为 48%[34-62%]和 35%[20-53%]。正常脑电图的 PPV 为 72%[68-76%]。在合作不佳的患者(SE 和癫痫发作;p<0.001)、插管和老年患者(SE;p<0.001)以及确诊癫痫患者(癫痫发作;p=0.004)中,SE 和癫痫发作的检测受到影响。脑电图技术员识别出癫痫发作特征的假阴性很少,但假阳性很多,并且识别出正常脑电图的 PPV 很好。脑电图技术员报告无癫痫发作特征可能令人安心;然而,在采取行动之前,脑电图记录应由神经生理学家进行审查。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/671d/8238944/42bfc2df602b/41598_2021_92827_Fig1_HTML.jpg

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