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EEG in the critical care setting.

Lawrence J Hirsch1, Margaret T Gopaul2

  • 1Comprehensive Epilepsy Center, Department of Neurology, Yale University School of Medicine, New Haven, CT, USA.

Clinical Neurophysiology : Official Journal of the International Federation of Clinical Neurophysiology
|November 26, 2025
PubMed
Summary
This summary is machine-generated.

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Continuous electroencephalography (cEEG) in the ICU detects seizures in 10-20% of patients, often without symptoms. Higher seizure burden predicts worse outcomes, but AI tools and standardization can improve access and patient care.

Area of Science:

  • Neuroscience
  • Critical Care Medicine
  • Clinical Neurophysiology

Background:

  • Continuous electroencephalography (cEEG) use is rising in intensive care units (ICUs).
  • Implementation and interpretation of cEEG remain inconsistent.
  • Understanding cEEG's clinical impact is crucial for optimizing patient care.

Purpose of the Study:

  • To review the role of cEEG in diagnosis, prognostication, and treatment in critical care.
  • To evaluate the effectiveness of cEEG in identifying nonconvulsive seizures and predicting outcomes.
  • To explore the potential of advanced EEG technologies and artificial intelligence (AI) in critical care neurophysiology.

Main Methods:

  • Conducted a narrative review of observational studies, randomized controlled trials, and consensus recommendations.
Keywords:
Continuous EEGIntensive care unitNonconvulsive seizuresPrognosisSeizure burdenStatus epilepticus

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  • Included adult and pediatric critical care populations.
  • Analyzed data on seizure detection, burden, and outcome prediction.

    • Main Results:

    • Nonconvulsive seizures occur in 10-20% of ICU patients on cEEG, frequently without clinical signs.
    • Higher seizure burden (e.g., >12 min/hour) predicts poor outcomes like mortality and cognitive impairment.
    • Rapid-response EEG and AI tools enhance diagnostic efficiency and access.
    • Quantitative EEG detects acute brain events like ischemia earlier than other methods.

    Conclusions:

    • cEEG has significantly advanced seizure detection and outcome prediction in the ICU.
    • Gaps in access, workforce, interpretation, and implementation need addressing.
    • Standardization, point-of-care devices, and AI integration are key to expanding cEEG's benefits and improving patient outcomes.