A Trial of Real-Time Electrographic Seizure Detection by Neuro-ICU Nurses Using a Panel of Quantitative EEG Trends

  • Jennifer H. KangEmail author
  • G. Clay Sherill
  • Saurabh R. Sinha
  • Christa B. Swisher
Original Work



Non-convulsive seizures (NCS) are a common occurrence in the neurologic intensive care unit (Neuro-ICU) and are associated with worse outcomes. Continuous electroencephalogram (cEEG) monitoring is necessary for the detection of NCS; however, delays in interpretation are a barrier to early treatment. Quantitative EEG (qEEG) calculates a time-compressed simplified visual display from raw EEG data. This study aims to evaluate the performance of Neuro-ICU nurses utilizing bedside, real-time qEEG interpretation for detecting recurrent NCS.


This is a prospective, single-institution study of patients admitted to the Duke Neuro-ICU between 2016 and 2018 who had NCS identified on traditional cEEG review. The accuracy of recurrent seizure detection on hourly qEEG review by bedside Neuro-ICU nurses was compared to the gold standard of cEEG interpretation by two board-certified neurophysiologists. The nurses first received brief qEEG training, individualized for their specific patient. The bedside qEEG display consisted of rhythmicity spectrogram (left and right hemispheres) and amplitude-integrated EEG (left and right hemispheres) in 1-h epochs.


Twenty patients were included and 174 1-h qEEG blocks were analyzed. Forty-seven blocks contained seizures (27%). The sensitivity was 85.1% (95% CI 71.1–93.1%), and the specificity was 89.8% (82.8–94.2%) for the detection of seizures for each 1-h block when compared to interpretation of conventional cEEG by two neurophysiologists. The false positive rate was 0.1/h. Hemispheric seizures (> 4 unilateral EEG electrodes) were more likely to be correctly identified by nurses on qEEG than focal seizures (≤ 4 unilateral electrodes) (p = 0.03).


After tailored training sessions, Neuro-ICU nurses demonstrated a good sensitivity for the interpretation of bedside real-time qEEG for the detection of recurrent NCS with a low false positive rate. qEEG is a promising tool that may be used by non-neurophysiologists and may lead to earlier detection of NCS.


Quantitative EEG qEEG Seizures ICU EEG Non-convulsive seizures 



The authors would like to acknowledge the Donald B. Sanders Neurology Fellows Research Grant for research funding support, Kristina Balderson for data acquisition assistance, and Michael W. Lutz, Ph.D. for statistical support.

Authors’ Contributions

JHK: involved in acquisition of data, analysis and interpretation of data, drafting of manuscript, and final approval of version to be published. GCS: performed conception and design, acquisition of data, revision of manuscript critically for important intellectual content, and final approval of the manuscript to be published. CBS: carried out conception and design, acquisition of data, analysis of data, revision of manuscript critically for important intellectual content, and final approval of the version to be published. SRS: took part in conception and design, analysis of data, revision of manuscript critically for important intellectual content, and final approval of the version to be published.

Source of Support

This study was funded by the Donald B. Sanders Neurology Fellows Research Grant (Internal grant within Duke University).

Conflict of interest

Jennifer H. Kang, MD, and G. Clay Sherill have none to declare. Christa B. Swisher, MD has received speaker’s honorarium from UCB and Eisai. Saurabh R. Sinha, MD, Ph.D. reports grants and personal fees from UCB Pharmaceuticals, grants from Eisai Inc., personal fees from Cadwell Inc., personal fees from Monteris Inc., grants from Neuropace Inc., grants from Marinus Pharmaceuticals, personal fees from Springer Publishing, other from American Clinical Neurophysiology Society, other from American Board of Clinical Neurophysiology, and other from ABRET Neurodiagnostic Credentialing and Accreditation, outside the submitted work. None are related to this work.

Ethical Approval

This study was approved by the Duke Institutional Review Board prior to the initiation of participant enrollment.

Supplementary material

12028_2019_673_MOESM1_ESM.docx (46 kb)
Supplementary Fig. 1. Seizure rate and Neuro-ICU nurse performance for each patient. For each patient listed in each row, the seizure rate per hour based on neurophysiologist review is denoted by color (see Key). A shaded box indicates the Neuro-ICU nurse reported an incorrect seizure assessment for that hour. Each box is 1 h of time. (DOCX 45 kb)


  1. 1.
    Friedman D, Claassen J, Hirsch LJ. Continuous electroencephalogram monitoring in the intensive care unit. Anesth Analg. 2009;109(2):506–23.Google Scholar
  2. 2.
    Claassen J, Mayer SA, Kowalski RG, Emerson RG, Hirsch LJ. Detection of electrographic seizures with continuous EEG monitoring in critically ill patients. Neurology. 2004;62(10):1743–8.Google Scholar
  3. 3.
    Towne AR, Waterhouse EJ, Boggs JG, et al. Prevalence of nonconvulsive status epilepticus in comatose patients. Neurology. 2000;54(2):340–5.Google Scholar
  4. 4.
    DeLorenzo RJ, Waterhouse EJ, Towne AR, et al. Persistent nonconvulsive status epilepticus after the control of convulsive status epilepticus. Epilepsia. 1998;39(8):833–40.Google Scholar
  5. 5.
    Vespa PM, Miller C, McArthur D, et al. Nonconvulsive electrographic seizures after traumatic brain injury result in a delayed, prolonged increase in intracranial pressure and metabolic crisis. Crit Care Med. 2007;35(12):2830–6.Google Scholar
  6. 6.
    Gutierrez-Viedma A, Parejo-Carbonell B, Cuadrado ML, et al. The relevance of timing in nonconvulsive status epilepticus: a series of 38 cases. Epilepsy Behav. 2018;82:11–6.Google Scholar
  7. 7.
    Cheng JY. Latency to treatment of status epilepticus is associated with mortality and functional status. J Neurol Sci. 2016;370:290–5.Google Scholar
  8. 8.
    Mazarati AM, Baldwin RA, Sankar R, Wasterlain CG. Time-dependent decrease in the effectiveness of antiepileptic drugs during the course of self-sustaining status epilepticus. Brain Res. 1998;814(1–2):179–85.Google Scholar
  9. 9.
    Sanchez Fernandez I, Gainza-Lein M, Abend NS, et al. Factors associated with treatment delays in pediatric refractory convulsive status epilepticus. Neurology. 2018;90(19):e1692–701.Google Scholar
  10. 10.
    Brophy GM, Bell R, Claassen J, et al. Guidelines for the evaluation and management of status epilepticus. Neurocrit Care. 2012;17(1):3–23.Google Scholar
  11. 11.
    Glauser T, Shinnar S, Gloss D, et al. Evidence-based guideline: treatment of convulsive status epilepticus in children and adults: report of the Guideline Committee of the American Epilepsy Society. Epilepsy Curr. 2016;16(1):48–61.Google Scholar
  12. 12.
    Hill CE, Parikh AO, Ellis C, Myers JS, Litt B. Timing is everything: where status epilepticus treatment fails. Ann Neurol. 2017;82(2):155–65.Google Scholar
  13. 13.
    Westover MB, Shafi MM, Bianchi MT, et al. The probability of seizures during EEG monitoring in critically ill adults. Clin Neurophysiol. 2015;126(3):463–71.Google Scholar
  14. 14.
    Haider HA, Esteller R, Hahn CD, et al. Sensitivity of quantitative EEG for seizure identification in the intensive care unit. Neurology. 2016;87(9):935–44.Google Scholar
  15. 15.
    Gavvala J, Abend N, LaRoche S, et al. Continuous EEG monitoring: a survey of neurophysiologists and neurointensivists. Epilepsia. 2014;55(11):1864–71.Google Scholar
  16. 16.
    Swisher CB, Sinha SR. Utilization of quantitative EEG trends for critical care continuous EEG monitoring: a survey of neurophysiologists. J Clin Neurophysiol. 2016;33(6):538–44.Google Scholar
  17. 17.
    Swisher CB, White CR, Mace BE, et al. Diagnostic accuracy of electrographic seizure detection by neurophysiologists and non-neurophysiologists in the adult ICU using a panel of quantitative EEG trends. J Clin Neurophysiol. 2015;32(4):324–30.Google Scholar
  18. 18.
    Amorim E, Williamson CA, Moura L, et al. Performance of spectrogram-based seizure identification of adult EEGs by critical care nurses and neurophysiologists. J Clin Neurophysiol. 2017;34(4):359–64.Google Scholar
  19. 19.
    Lalgudi Ganesan S, Stewart CP, Atenafu EG, et al. Seizure identification by critical care providers using quantitative electroencephalography. Crit Care Med. 2018;46(12):e1105–11.Google Scholar
  20. 20.
    Sinha SR. Quantitative EEG principles. In: LaRoche SM, editor. Handbook of ICU EEG monitoring. New York: Demos Medical Publishing; 2013. p. 221–7.Google Scholar
  21. 21.
    Leitinger M, Beniczky S, Rohracher A, et al. Salzburg consensus criteria for non-convulsive status epilepticus—approach to clinical application. Epilepsy Behav. 2015;49:158–63.Google Scholar
  22. 22.
    Sinha SR, Smart SO, Husain AM. Seizure burden score: a quantitative description of seizure intensity in continuous EEG recordings. Epilepsia. 2013;54(Suppl 6):106–24.Google Scholar
  23. 23.
    Vespa PM, Nuwer MR, Nenov V, et al. Increased incidence and impact of nonconvulsive and convulsive seizures after traumatic brain injury as detected by continuous electroencephalographic monitoring. J Neurosurg. 1999;91(5):750–60.Google Scholar
  24. 24.
    De Marchis GM, Pugin D, Meyers E, et al. Seizure burden in subarachnoid hemorrhage associated with functional and cognitive outcome. Neurology. 2016;86(3):253–60.Google Scholar
  25. 25.
    Payne ET, Zhao XY, Frndova H, et al. Seizure burden is independently associated with short term outcome in critically ill children. Brain. 2014;137(Pt 5):1429–38.Google Scholar
  26. 26.
    McBride MC, Laroia N, Guillet R. Electrographic seizures in neonates correlate with poor neurodevelopmental outcome. Neurology. 2000;55(4):506–13.Google Scholar
  27. 27.
    Pisani F, Copioli C, Di Gioia C, Turco E, Sisti L. Neonatal seizures: relation of ictal video-electroencephalography (EEG) findings with neurodevelopmental outcome. J Child Neurol. 2008;23(4):394–8.Google Scholar
  28. 28.
    Rao SK, Mahulikar A, Ibrahim M, et al. Inadequate benzodiazepine dosing may result in progression to refractory and non-convulsive status epilepticus. Epileptic Disord. 2018;20(4):265–9.Google Scholar
  29. 29.
    Abend NS, Gutierrez-Colina AM, Topjian AA, et al. Nonconvulsive seizures are common in critically ill children. Neurology. 2011;76(12):1071–7.Google Scholar
  30. 30.
    Akman CI, Micic V, Thompson A, Riviello JJ Jr. Seizure detection using digital trend analysis: factors affecting utility. Epilepsy Res. 2011;93(1):66–72.Google Scholar
  31. 31.
    Nitzschke R, Muller J, Engelhardt R, Schmidt GN. Single-channel amplitude integrated EEG recording for the identification of epileptic seizures by nonexpert physicians in the adult acute care setting. J Clin Monit Comput. 2011;25(5):329–37.Google Scholar
  32. 32.
    Rennie JM, Chorley G, Boylan GB, et al. Non-expert use of the cerebral function monitor for neonatal seizure detection. Arch Dis Child Fetal Neonatal Ed. 2004;89(1):F37–40.Google Scholar
  33. 33.
    Shellhaas RA, Soaita AI, Clancy RR. Sensitivity of amplitude-integrated electroencephalography for neonatal seizure detection. Pediatrics. 2007;120(4):770–7.Google Scholar
  34. 34.
    Williamson CA, Wahlster S, Shafi MM, Westover MB. Sensitivity of compressed spectral arrays for detecting seizures in acutely ill adults. Neurocrit Care. 2014;20(1):32–9.Google Scholar
  35. 35.
    Evans E, Koh S, Lerner J, Sankar R, Garg M. Accuracy of amplitude integrated EEG in a neonatal cohort. Arch Dis Child Fetal Neonatal Ed. 2010;95(3):F169–73.Google Scholar

Copyright information

© This is a U.S. government work and its text is not subject to copyright protection in the United States; however, its text may be subject to foreign copyright protection 2019

Authors and Affiliations

  1. 1.Department of NeurologyDuke University Medical CenterDurhamUSA
  2. 2.Neurodiagnostic CenterVeterans Affairs Medical CenterDurhamUSA

Personalised recommendations