Seizure detection using digital trend analysis: Factors affecting utility
Seizure detection using digital trend analysis: Factors affecting utility
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DOI：
10.1016/j.eplepsyres.2010.10.018
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发表时间：
2011-01-01
影响因子：
2.2
通讯作者：
Riviello, James J., Jr.
中科院分区：
文献类型：
--
作者：
Akman, Cigdem I.;Micic, Vesna;Riviello, James J., Jr.
背景：脑电图监测对于危重症过程中癫痫发作的早期发现非常重要。然而，真实的时间EEG解释的逻辑对于神经生理学和重症监护医学团队是具有挑战性的。本研究评估了影响数字趋势分析（DTA）的效用快速癫痫发作identification in children.Methods：数字EEG文件中的危重病儿童癫痫发作DTA检索的因素。包络趋势（ET）和压缩频谱阵列（CSA）应用于原始EEG数据，并提供给经验丰富和缺乏经验的用户进行解释，这些用户对常规EEG结果不知情。EEG结果与和不存在的癫痫发作和癫痫发作的特点进行了analysed.Results：我们发现，一些因素影响准确的癫痫发作检测，包括相关的因素解释的经验，显示大小和类型的DTA方法用于分析，除了基线EEG结果。ET更依赖于用户体验，此外，与无经验用户相比，显示尺寸和多模式DTA应用（CSA和ET组合）增加了有经验用户癫痫发作检测的灵敏度。在没有常规EEG记录的情况下，将伪影报告为癫痫发作，无论经验如何。最大尖峰振幅、发作持续时间和发作频率是准确性的其他重要决定因素。短持续时间的电图癫痫发作更好地检测ET，最大棘波幅度是重要的ET和CSA。两种数字趋势分析方法均可轻松检测到重复性癫痫发作。伪影可能被报告为癫痫发作，无论经验，如果传统的EEG记录是不可用的interpretation.Conclusion：DTA应用到原始EEG数据确实产生一个图形显示，便于识别癫痫发作。电描记癫痫发作的实际特征可以预测哪种DTA方法更好，并且当同时使用多模态趋势时，癫痫发作检测的整体准确性可以增加。DTA单独应用与常规EEG显示有利于快速解释EEG结果，而无需考虑经验。(C)2010 Elsevier B.V.保留所有权利。
Background: EEG monitoring is important for the early detection of seizures during the course of critical illness. However, the logistics of real time EEG interpretation is challenging for the neurophysiology and critical care medicine teams. This study evaluated factors affecting the utility of digital trend analysis (DTA) for rapid seizure identification in children.Methods: Digital EEG files of seizures in critically ill children were retrieved for DTA. The envelop trend (ET) and compressed spectral array (CSA) were applied to the raw EEG data and presented to an experienced and inexperienced user for interpretation who were blinded to conventional EEG findings. The EEG findings with and without presence of seizures and features of seizures were analyzed.Results: We found that a number of factors affected accurate seizure detection including factors related to interpreter's experiences, display size and type of DTA methods used for analysis in addition to baseline EEG findings. ET was more dependent on user experience, furthermore, display size and multimodal DTA application (CSA and ET combined) increased the sensitivity of seizure detection for the experienced user compared to inexperience users. The artifacts were reported as seizures regardless of experience without presence of conventional EEG recording. The maximum spike amplitude, seizure duration, and seizure frequency were other important determinants for accuracy. Electrographic seizures with shorter duration were better detected by ET, and the maximum spike amplitude was important for both the ET and CSA. Repetitive seizures are readily detected by both digital trending methods. Artifacts may be reported as seizures regardless of experience if conventional EEG recording is not available for the interpretation.Conclusion: DTA applied to the raw EEG data does produce a graphic display that facilitates identification of seizures. The actual characteristics of the electrographic seizure may predict which DTA method is better and the overall accuracy of seizure detection may increase when multimodal trending is used simultaneously. Application of DTA alone with display of conventional EEG is beneficial for rapid interpretation of EEG findings regardless of experience. (C) 2010 Elsevier B.V. All rights reserved.