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    Original Investigation
    Critical Care Medicine
    April 28, 2020

    Sensitivity of Continuous Electroencephalography to Detect Ictal Activity After Cardiac Arrest

    Author Affiliations
    • 1Department of Emergency Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
    • 2Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
    • 3Department of Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania
    • 4Department of Neurology, Massachusetts General Hospital, Boston
    • 5Department of Neurology, University of Wisconsin, Madison
    • 6Department of Neurology, Pittsburgh VA Medical Center, Pittsburgh, Pennsylvania
    • 7Department of Emergency Medicine, University of Alabama at Birmingham School of Medicine
    JAMA Netw Open. 2020;3(4):e203751. doi:10.1001/jamanetworkopen.2020.3751
    Key Points español 中文 (chinese)

    Question  Does continuous electroencephalographic (EEG) monitoring improve detection of epileptiform events associated with neurological outcome or potentially treatable seizure among patients resuscitated from cardiac arrest compared with brief intermittent EEG?

    Findings  In this cohort study including 759 patients who were resuscitated from cardiac arrest, continuous monitoring for nearly 48 hours was needed to achieve 95% sensitivity for prognostic epileptiform events; compared with brief intermittent EEG, continuous monitoring did not improve prediction of outcome at hospital discharge. Potentially treatable seizures were uncommon and rarely detected by brief intermittent monitoring.

    Meaning  Compared with continuous EEG, brief intermittent EEG is insensitive for detection of potentially treatable seizures after cardiac arrest but may be sufficient to guide multimodality prediction of outcome at hospital discharge.


    Importance  Epileptiform electroencephalographic (EEG) patterns are common after resuscitation from cardiac arrest, are associated with patient outcome, and may require treatment. It is unknown whether continuous EEG monitoring is needed to detect these patterns or if brief intermittent monitoring is sufficient. If continuous monitoring is required, the necessary duration of observation is unknown.

    Objective  To quantify the time-dependent sensitivity of continuous EEG for epileptiform event detection, and to compare continuous EEG to several alternative EEG-monitoring strategies for post–cardiac arrest outcome prediction.

    Design, Setting, and Participants  This observational cohort study was conducted in 2 academic medical centers between September 2010 and January 2018. Participants included 759 adults who were comatose after being resuscitated from cardiac arrest and who underwent 24 hours or more of EEG monitoring.

    Main Outcomes and Measures  Epileptiform EEG patterns associated with neurological outcome at hospital discharge, such as seizures likely to cause secondary injury.

    Results  Overall, 759 patients were included in the analysis; 281 (37.0%) were female, and the mean (SD) age was 58 (17) years. Epileptiform EEG activity was observed in 414 participants (54.5%), of whom only 26 (3.4%) developed potentially treatable seizures. Brief intermittent EEG had an estimated 66% (95% CI, 62%-69%) to 68% (95% CI, 66%-70%) sensitivity for detection of prognostic epileptiform events. Depending on initial continuity of the EEG background, 0 to 51 hours of monitoring were needed to achieve 95% sensitivity for the detection of prognostic epileptiform events. Brief intermittent EEG had a sensitivity of 7% (95% CI, 4%-12%) to 8% (95% CI, 4%-12%) for the detection of potentially treatable seizures, and 0 to 53 hours of continuous monitoring were needed to achieve 95% sensitivity for the detection of potentially treatable seizures. Brief intermittent EEG results yielded similar information compared with continuous EEG results when added to multivariable models predicting neurological outcome.

    Conclusions and Relevance  Compared with continuous EEG monitoring, brief intermittent monitoring was insensitive for detection of epileptiform events. Monitoring EEG results significantly improved multimodality prediction of neurological outcome, but continuous monitoring appeared to add little additional information compared with brief intermittent monitoring.