Pitfalls in EEG Analysis in Patients With Nonconvulsive Status Epilepticus: A Preliminary Study

Ying Wang (Corresponding author), Ivan C. Zibrandtsen, Richard H.C. Lazeron, Johannes P. van Dijk, Xi Long, Ronald M. Aarts, Lei Wang, Johan B.A.M. Arends

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Objective: Electroencephalography (EEG) interpretations through visual (by human raters) and automated (by computer technology) analysis were still not reliable for the diagnosis of nonconvulsive status epilepticus (NCSE). This study aimed to identify typical pitfalls in the EEG analysis and make suggestions as to how those pitfalls might be avoided. Methods: We analyzed the EEG recordings of individuals who had clinically confirmed or suspected NCSE. Epileptiform EEG activity during seizures (ictal discharges) was visually analyzed by 2 independent raters. We investigated whether unreliable EEG visual interpretations quantified by low interrater agreement can be predicted by the characteristics of ictal discharges and individuals’ clinical data. In addition, the EEG recordings were automatically analyzed by in-house algorithms. To further explore the causes of unreliable EEG interpretations, 2 epileptologists analyzed EEG patterns most likely misinterpreted as ictal discharges based on the differences between the EEG interpretations through the visual and automated analysis. Results: Short ictal discharges with a gradual onset (developing over 3 s in length) were liable to be misinterpreted. An extra 2 min of ictal discharges contributed to an increase in the kappa statistics of >0.1. Other problems were the misinterpretation of abnormal background activity (slow-wave activities, other abnormal brain activity, and the ictal-like movement artifacts), continuous interictal discharges, and continuous short ictal discharges. Conclusion: A longer duration criterion for NCSE-EEGs than 10 s that is commonly used in NCSE working criteria is recommended. Using knowledge of historical EEGs, individualized algorithms, and context-dependent alarm thresholds may also avoid the pitfalls.

Original languageEnglish
Pages (from-to)255-264
Number of pages10
JournalClinical EEG and Neuroscience
Issue number3
Publication statusPublished - 1 May 2023

Bibliographical note

Funding Information:
The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work is part of the research program BrainWave with project number 14714, which is (partly) financed by the Netherlands Organization for Scientific Research (NWO). This work was supported by the Stichting voor de Technische Wetenschappen (grant number 14714).


  • interrater agreement
  • misinterpretation
  • NCSE
  • reliability
  • seizure


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  • Wearable Brainwave Processing Platform

    Bergmans, J. W. M. (Project Manager), van der Hagen, D. (Project communication officer), Sánchez Martín, V. (Program Manager), Corporaal, H. (Project member), Pineda de Gyvez, J. (Project member) & Huisken, J. A. (Project member)


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  • Brainwave

    Huisken, J. A. (Project member), Jiao, H. (Project Manager), Singh, K. (Project member), Sánchez Martín, V. (Project Manager), de Bruin, E. (Project member), van der Hagen, D. (Project communication officer) & de Mol-Regels, M. (Project communication officer)


    Project: Research direct

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