Skip to main content

Advertisement

SpringerLink
Log in

Continuous Electroencephalogram Evaluation of Paroxysmal Events in Critically Ill Patients: Diagnostic Yield and Impact on Clinical Decision Making

  • Original work
  • Published:
Neurocritical Care Aims and scope Submit manuscript

Abstract

Background

Continuous electroencephalogram (cEEG) monitoring has been widely used in the intensive care unit (ICU) for the evaluation of patients in the ICU with altered consciousness to detect nonconvulsive seizures. We investigated the yield of cEEG when used to evaluate paroxysmal events in patients in the ICU and assessed the predictors of a diagnostic findings. The clinical impact of cEEG was also evaluated in this study.

Methods

We identified patients in the ICU who underwent cEEG monitoring (> 6 h) to evaluate paroxysmal events between January 1, 2018, and December 31, 2019. We extracted patient demographics, medical history, neurological examination, brain imaging results, and the description of the paroxysmal events that necessitated the monitoring. We dichotomized the cEEG studies into those that captured habitual nonepileptic events or revealed epileptiform discharges (ictal or interictal), i.e., those considered to be of positive diagnostic yield (Y +), and those studies that did not show those findings (negative diagnostic yield, Y −). We also assessed the clinical impact of cEEG by documenting changes in administered antiseizure medication (ASM) before and after the cEEG.

Results

We identified 159 recordings that were obtained for the indication of paroxysmal events, of which abnormal movements constituted the majority (n = 123). For the remaining events (n = 36), descriptions included gaze deviations, speech changes, and sensory changes. Twenty-nine percent (46 of 159) of the recordings were Y + , including the presence of ictal or interictal epileptiform discharges (n = 33), and captured habitual nonepileptic events (n = 13). A history of epilepsy was the only predictor of the study outcome. Detection of abnormal findings occurred within 6 h of the recording in most patients (30 of 46, 65%). Overall, cEEG studies led to 49 (31%) changes in ASM administration. The changes included dosage increases or initiation of ASM in patients with epileptiform discharges (n = 28) and reduction or elimination of ASM in patients with either habitual nonepileptic events (n = 5) or Y − cEEG studies (n = 16).

Conclusions

Continuous electroencephalogram monitoring is valuable in evaluating paroxysmal events, with a diagnostic yield of 29% in critically ill patients. A history of epilepsy predicts diagnostic studies. Both Y + and Y − cEEG studies may directly impact clinical decisions by leading to ASMs changes.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  1. Claassen J, Mayer SA, Kowalski RG, et al. Detection of electrographic seizures with continuous EEG monitoring in critically ill patients. Neurology. 2004;62(10):1743–8.

    Article  CAS  PubMed  Google Scholar 

  2. Herman ST, Abend NS, Bleck TP, et al. Critical care continuous EEG task force of the American clinical neurophysiology society. Consensus statement on continuous EEG in critically ill adults and children, part I: indications. J Clin Neurophysiol. 2015;32(2):87–95.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Alvarez V, Rodriguez Ruiz AA, LaRoche S, et al. Critical care EEG monitoring research consortium (CCEMRC). The use and yield of continuous EEG in critically ill patients: a comparative study of three centers. Clin Neurophysiol. 2017;128(4):570–8.

    Article  PubMed  Google Scholar 

  4. Billakota S, Sinha S. Utility of continuous EEG monitoring in noncritically ill hospitalized patients. J Clin Neurophysiol. 2016;33(5):421–5.

    Article  PubMed  Google Scholar 

  5. Callaway CW, Donnino MW, Fink EL, et al. Part 8: cardiac arrest care: 2015 American heart association guidelines update for cardiopulmonary resuscitation and emergency cardiovascular care. Circulation. 2015;132(18 Suppl 2):S465–82.

    PubMed  PubMed Central  Google Scholar 

  6. Westhall E, Rossetti AO, van Rootselaar AF, et al. Standardized EEG interpretation accurately predicts prognosis after cardiac arrest. Neurology. 2016;86(16):1482–90.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Florea B, Beniczky SA, Demény H, et al. Semiology of subtle motor phenomena in critically ill patients. Seizure. 2017;48:33–5.

    Article  PubMed  Google Scholar 

  8. Hanrahan B, Ghearing G, Urban A, et al. Diagnostic accuracy of paroxysmal spells: clinical history versus observation. Epilepsy Behav. 2018;78:73–7.

    Article  PubMed  Google Scholar 

  9. Hannawi Y, Abers MS, Geocadin RG, et al. Abnormal movements in critical care patients with brain injury: a diagnostic approach. Crit Care. 2016;20:60.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Benbadis S, Chen S, Melo M. What’s shaking in the ICU? The differential diagnosis of seizures in the intensive care setting. Epilepsia. 2010;51(11):2338–40.

    Article  PubMed  Google Scholar 

  11. Pellinen J, Tafuro E, Yang A, et al. Focal nonmotor versus motor seizures: the impact on diagnostic delay in focal epilepsy. Epilepsia. 2020;61(12):2643–52.

    Article  PubMed  Google Scholar 

  12. Zee DS, Leigh JR. The neurology of eye movements. 3rd ed. NewYork: Oxford University Press; 1999.

    Google Scholar 

  13. Gabr M, Lüders H, Dinner D, et al. Speech manifestations in lateralization of temporal lobe seizures. Ann Neurol. 1989;25(1):82–7.

    Article  CAS  PubMed  Google Scholar 

  14. Schmitt SE. Utility of clinical features for the diagnosis of seizures in the intensive care unit. J Clin Neurophysiol. 2017;34(2):158–61.

    Article  PubMed  Google Scholar 

  15. Pandian JD, Cascino GD, So EL, et al. Digital video electroencephalographic monitoring in the neurological neurosurgical intensive care unit: clinical features and outcome. Arch Neurol. 2004;61(7):1090–4.

    Article  PubMed  Google Scholar 

  16. Benbadis SR, O’Neill E, Tatum WO, et al. Outcome of prolonged video-EEG monitoring at a typical referral epilepsy center. Epilepsia. 2004;45(9):1150–3.

    Article  PubMed  Google Scholar 

  17. Ghougassian DF, d’Souza W, Cook MJ, et al. Evaluating the utility of inpatient video-EEG monitoring. Epilepsia. 2004;45(8):928–32.

    Article  PubMed  Google Scholar 

  18. Dash D, Hernandez-Ronquillo L, Moien-Afshari F, et al. Ambulatory EEG: a cost-effective alternative to inpatient video-EEG in adult patients. Epileptic Disord. 2012;14(3):290–7.

    Article  PubMed  Google Scholar 

  19. Lawley A, Manfredonia F, Cavanna AE. Video-ambulatory EEG in a secondary care center: a retrospective evaluation of utility in the diagnosis of epileptic and nonepileptic seizures. Epilepsy Behav. 2016;57(Pt A):137–40.

    Article  PubMed  Google Scholar 

  20. Lobello K, Morgenlander JC, Radtke RA, et al. Video/EEG monitoring in the evaluation of paroxysmal behavioral events: duration, effectiveness, and limitations. Epilepsy Behav. 2006;8(1):261–6.

    Article  PubMed  Google Scholar 

  21. Primiani CT, Rivera-Cruz A, Trudeau P, et al. The yield of ambulatory EEG-video monitoring. Clin EEG Neurosci. 2021;52(4):274–9.

    Article  PubMed  Google Scholar 

  22. Syed TU, LaFrance WC Jr, Loddenkemper T, et al. Outcome of ambulatory video-EEG monitoring in a 10,000 patient nationwide cohort. Seizure. 2019;66:104–11.

    Article  PubMed  Google Scholar 

  23. Newey C, Kinzy T, Punia V, et al. Continuous electroencephalography in the critically ill: clinical and continuous electroencephalography markers for targeted monitoring. J Clin Neurophysiol. 2018;35(4):325–31.

    Article  PubMed  Google Scholar 

  24. Betjemann JP, Nguyen I, Santos-Sanchez C, et al. Diagnostic yield of electroencephalography in a general inpatient population. Mayo Clin Proc. 2013;88(4):326–31.

    Article  PubMed  Google Scholar 

  25. Mikhaeil-Demo Y, Gonzalez Otarula KA, et al. Indications and yield of ambulatory EEG recordings. Epileptic Disord. 2021;23(1):94–103.

    Article  PubMed  Google Scholar 

  26. Robinson AA, Pitiyanuvath N, Abou-Khalil BW, et al. Predictors of a nondiagnostic epilepsy monitoring study and yield of repeat study. Epilepsy Behav. 2011;21(1):76–9.

    Article  PubMed  Google Scholar 

  27. Abend N, Topjian A, Gutierrez-Colina A, et al. Impact of continuous EEG monitoring on clinical management in critically ill children. Neurocrit Care. 2011;15(1):70–5.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Kilbride RD, Costello DJ, Chiappa KH. How seizure detection by continuous electroencephalographic monitoring affects the prescribing of antiepileptic medications. Arch Neurol. 2009;66(6):723–8.

    Article  PubMed  Google Scholar 

  29. Rossetti AO, Schindler K, Sutter R, et al. Continuous vs routine electroencephalogram in critically ill adults with altered consciousness and no recent Seizure: a multicenter randomized clinical trial. JAMA Neurol. 2020;77(10):1225–32.

    Article  PubMed  Google Scholar 

  30. Amin U, Benbadis SR. The role of EEG in the erroneous diagnosis of epilepsy. J Clin Neurophysiol. 2019;36(4):294–7.

    Article  PubMed  Google Scholar 

  31. Martin RC, Gilliam FG, Kilgore M, et al. Improved health care resource utilization following video-EEG-confirmed diagnosis of nonepileptic psychogenic seizures. Seizure. 1998;7:385–90.

    Article  CAS  PubMed  Google Scholar 

Download references

Funding

This work received no funding.

Author information

Authors and Affiliations

  1. Department of Neurology, George Washington University School of Medicine and Health Sciences, George Washington University, 2150 Pennsylvania Ave, NW, Washington, DC, 20037, USA

    Hai Chen, Eugenie Atallah, Jennifer Pauldurai, Andrew Becker & Mohamad Koubeissi

Authors
  1. Hai Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Eugenie Atallah
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jennifer Pauldurai
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Andrew Becker
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Mohamad Koubeissi
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Dr. Chen: design and implementation of the research, data analysis, and article writing. Drs. Atallah and Pauldurai: data collection. Dr. Becker: result discussion and article writing. Dr. Koubeissi: study design and article writing. The final manuscript was approved by all authors.

Corresponding author

Correspondence to Hai Chen.

Ethics declarations

Conflicts of Interest

The authors have no financial, consultant, or institutional conflicts of interest related to this study to declare.

Ethical approval/informed consent

We confirm adherence to ethical guidelines and indicate ethical approvals (institutional review board) and the use of informed consent, as appropriate. This study was approved by the George Washington University Institutional Review Board.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chen, H., Atallah, E., Pauldurai, J. et al. Continuous Electroencephalogram Evaluation of Paroxysmal Events in Critically Ill Patients: Diagnostic Yield and Impact on Clinical Decision Making. Neurocrit Care 37, 697–704 (2022). https://doi.org/10.1007/s12028-022-01542-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12028-022-01542-y

Keywords

Search

Navigation