Amsterdam University Medical Centers, University of Amsterdam, Department of Intensive Care, Amsterdam Neuroscience, Amsterdam, the Netherlands.
Amsterdam University Medical Centers, University of Amsterdam, Department of Neurology/Clinical Neurophysiology, Amsterdam Neuroscience, Amsterdam, the Netherlands.
Ann Neurol. 2019 Jul;86(1):17-27. doi: 10.1002/ana.25507. Epub 2019 Jun 8.
Outcome prediction in patients after cardiac arrest (CA) is challenging. Electroencephalographic reactivity (EEG-R) might be a reliable predictor. We aimed to determine the prognostic value of EEG-R using a standardized assessment.
In a prospective cohort study, a strictly defined EEG-R assessment protocol was executed twice per day in adult patients after CA. EEG-R was classified as present or absent by 3 EEG readers, blinded to patient characteristics. Uncertain reactivity was classified as present. Primary outcome was best Cerebral Performance Category score (CPC) in 6 months after CA, dichotomized as good (CPC = 1-2) or poor (CPC = 3-5). EEG-R was considered reliable for predicting poor outcome if specificity was ≥95%. For good outcome prediction, a specificity of ≥80% was used. Added value of EEG-R was the increase in specificity when combined with EEG background, neurological examination, and somatosensory evoked potentials (SSEPs).
Of 160 patients enrolled, 149 were available for analyses. Absence of EEG-R for poor outcome prediction had a specificity of 82% and a sensitivity of 73%. For good outcome prediction, specificity was 73% and sensitivity 82%. Specificity for poor outcome prediction increased from 98% to 99% when EEG-R was added to a multimodal model. For good outcome prediction, specificity increased from 70% to 89%.
EEG-R testing in itself is not sufficiently reliable for outcome prediction in patients after CA. For poor outcome prediction, it has no substantial added value to EEG background, neurological examination, and SSEPs. For prediction of good outcome, EEG-R seems to have added value. ANN NEUROL 2019.
心脏骤停(CA)后患者的预后预测具有挑战性。脑电图反应性(EEG-R)可能是一种可靠的预测指标。我们旨在使用标准化评估来确定 EEG-R 的预后价值。
在一项前瞻性队列研究中,对 CA 后成年患者每天进行两次严格定义的 EEG-R 评估方案。3 位 EEG 读者对患者特征进行盲法评估,将 EEG-R 分为存在或不存在。不确定的反应性被归类为存在。主要结局是 CA 后 6 个月的最佳脑功能预后评分(CPC),分为良好(CPC=1-2)或不良(CPC=3-5)。如果特异性≥95%,则认为 EEG-R 可靠预测不良预后。为了预测良好的预后,特异性≥80%。当 EEG-R 与 EEG 背景、神经系统检查和体感诱发电位(SSEP)相结合时,增加了特异性。
在纳入的 160 例患者中,149 例可进行分析。不良预后预测中 EEG-R 缺失的特异性为 82%,敏感性为 73%。对于良好的预后预测,特异性为 73%,敏感性为 82%。当 EEG-R 添加到多模态模型中时,不良预后预测的特异性从 98%增加到 99%。对于良好预后预测,特异性从 70%增加到 89%。
EEG-R 测试本身对于 CA 后患者的预后预测并不足够可靠。对于不良预后预测,它对 EEG 背景、神经系统检查和 SSEP 没有实质性的附加价值。对于良好预后的预测,EEG-R 似乎具有附加价值。