Department of Critical Care Medicine, The Hospital for Sick Children and University of Toronto, Toronto, ON, Canada.
Program in Neurosciences & Mental Health, The Hospital for Sick Children Research Institute, Toronto, ON, Canada.
Crit Care Med. 2018 Dec;46(12):e1105-e1111. doi: 10.1097/CCM.0000000000003385.
To compare the performance of critical care providers with that of electroencephalography experts in identifying seizures using quantitative electroencephalography display tools.
Diagnostic accuracy comparison among healthcare provider groups.
Multispecialty quaternary children's hospital in Canada.
ICU fellows, ICU nurses, neurophysiologists, and electroencephalography technologists.
Two-hour standardized one-on-one training, followed by a supervised individual review of 27 continuous electroencephalography recordings with the task of identifying individual seizures on eight-channel amplitude-integrated electroencephalography and color density spectral array displays.
Each participant reviewed 27 continuous electroencephalograms comprising 487 hours of recording containing a total of 553 seizures. Performance for seizure identification was compared among groups using a nested model analysis with adjustment for interparticipant variability within groups and collinearity among recordings. Using amplitude-integrated electroencephalography, sensitivity for seizure identification was comparable among ICU fellows (83.8%), ICU nurses (73.1%), and neurophysiologists (81.5%) but lower among electroencephalographic technologists (66.7%) (p = 0.003). Using color density spectral array, sensitivity was comparable among ICU fellows (82.4%), ICU nurses (88.2%), neurophysiologists (83.3%), and electroencephalographic technologists (73.3%) (p = 0.09). Daily false-positive rates were also comparable among ICU fellows (2.8 for amplitude-integrated electroencephalography, 7.7 for color density spectral array), ICU nurses (4.2, 7.1), neurophysiologists (1.2, 1.5), and electroencephalographic technologists (0, 0) (p = 0.41 for amplitude-integrated electroencephalography; p = 0.13 for color density spectral array). However, performance varied greatly across individual electroencephalogram recordings. Professional background generally played a greater role in determining performance than individual skill or electroencephalogram recording characteristics.
Following standardized training, critical care providers and electroencephalography experts displayed similar performance for identifying individual seizures using both amplitude-integrated electroencephalography and color density spectral array displays. Although these quantitative electroencephalographic trends show promise as a tool for bedside seizure screening by critical care providers, these findings require confirmation in a real-world ICU environment and in daily clinical use.
比较重症监护提供者和脑电图专家使用定量脑电图显示工具识别癫痫发作的表现。
医疗保健提供者组之间的诊断准确性比较。
加拿大多专科四级儿童医院。
ICU 研究员、ICU 护士、神经生理学家和脑电图技术员。
两小时标准化一对一培训，然后在监督下对 27 个连续脑电图记录进行个人审查，任务是在 8 通道幅度整合脑电图和彩色密度谱数组显示上识别单个癫痫发作。
每位参与者审查了 27 个连续脑电图，包含 487 小时的记录，总共有 553 次癫痫发作。使用嵌套模型分析比较了组间的癫痫识别性能，调整了组内参与者间变异性和记录之间的共线性。使用幅度整合脑电图，癫痫识别的敏感性在 ICU 研究员（83.8%）、ICU 护士（73.1%）和神经生理学家（81.5%）之间相当，但脑电图技术员（66.7%）较低（p = 0.003）。使用彩色密度谱数组，敏感性在 ICU 研究员（82.4%）、ICU 护士（88.2%）、神经生理学家（83.3%）和脑电图技术员（73.3%）之间相当（p = 0.09）。ICU 研究员的每日假阳性率也相当（幅度整合脑电图为 2.8，彩色密度谱数组为 7.7），ICU 护士（4.2，7.1），神经生理学家（1.2，1.5）和脑电图技术员（0，0）（幅度整合脑电图的 p = 0.41；彩色密度谱数组的 p = 0.13）。然而，个体脑电图记录的表现差异很大。专业背景通常比个人技能或脑电图记录特征对表现的影响更大。
经过标准化培训，重症监护提供者和脑电图专家在使用幅度整合脑电图和彩色密度谱数组显示识别单个癫痫发作方面表现出相似的性能。尽管这些定量脑电图趋势显示出作为重症监护提供者床边癫痫筛查工具的潜力，但这些发现需要在现实世界的 ICU 环境和日常临床使用中得到证实。
