A matter of timing: EEG monitoring for neurological prognostication after cardiac arrest in the era of targeted temperature management

Khazanova, Darya; Douglas, Vanja C.; Amorim, Edilberto

doi:10.23736/s0375-9393.21.14793-5

Cited by 7 publications

(5 citation statements)

References 57 publications

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“…46 Khazanova et al reviewed the literature on eeg monitoring for neurological prognostication after cardiac arrest. 47 the authors highlighted that temporal evolution was a fundamental aspect of eeg interpretation because patterns associated with irreversible brain injury were occasionally observed in patients who achieved a good outcome. indeed, eeg monitoring acquired greater value if incorporated into a multimodal prognostication approach.…”

Section: Respirationmentioning

confidence: 99%

A year in review in Minerva Anestesiologica 2019. Critical care

et al. 2020

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Section: Respirationmentioning

confidence: 99%

A year in review in Minerva Anestesiologica 2019. Critical care

et al. 2020

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“…3,4 Cardiac arrest is one of the few medical conditions in which continuous brain monitoring with EEG is routinely started within a few hours from coma onset. 5,6 This feature of current clinical practice affords the unique opportunity to observe the longitudinal evolution of the neurophysiology of coma recovery before neurologic improvement is perceptible to clinicians, creating new avenues for studying coma neuroscience at a scale and resolution not possible for other acute coma etiologies. 5,[7][8][9] Coma neurophysiology research using EEG for chronic disorders of consciousness and general anesthesia has provided critical insights about the evolution of neural processes involved in conscious awareness.…”

Section: Introductionmentioning

confidence: 99%

“…5,8,9,18 These patterns are associated with poor neurologic outcomes, but some patients may recover despite injury causing this type of physiology. 6,19,20 To advance the current management of acute brain injury and identify patients with potential for coma recovery despite unfavorable EEG patterns, we must understand the wide range of concurrent neurophysiologic processes contributing to acute coma soon after brain injury and their temporal changes.…”

Section: Introductionmentioning

confidence: 99%

Neurophysiology State Dynamics Underlying Acute Neurologic Recovery After Cardiac Arrest

et al. 2023

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Background and Objectives:Epileptiform activity and burst suppression are neurophysiology signatures reflective of severe brain injury following cardiac arrest. We aimed to delineate the evolution of coma neurophysiology features ensembles associated with recovery from coma after cardiac arrest.Methods:Adult subjects in acute coma following cardiac arrest were included in a retrospective database involving seven hospitals. The combination of three quantitative EEG features (burst suppression ratio [BSup], spike frequency [SpF], and Shannon’s entropy [En]) was used to define five distinct neurophysiology states: Epileptiform High Entropy (EHE: SpF ≥4/minute and En ≥5); Epileptiform and Low Entropy (ELE: SpF ≥4/minute and <5 En); Non-Epileptiform High Entropy (NEHE: SpF <4/minute and ≥5 En); Non-Epileptiform Low Entropy (NELE: SpF<4/minute and <5 En), and Burst Suppression (BSup≥50% and SpF <4/minute). State transitions were measured at consecutive 6h blocks between 6-84h after return of spontaneous circulation. Good neurological outcome was defined as best Cerebral Performance Category (CPC) 1-2 at 3-6 months.Results:One-thousand thirty-eight subjects were included (50,224 hours of EEG), and 373 (36%) had good outcome. Subjects with EHE state had a 29% rate of good outcome while those with ELE had 11%. Transitions out of an EHE or BSup to a NEHE were associated with good outcome (45% and 20%, respectively). No subjects with ELE state lasting >15h had good recovery.Discussion:Transition to high entropy states is associated with increased likelihood of good outcome despite preceding epileptiform or burst suppression states. High entropy may reflect mechanisms of resilience to hypoxic-ischemic brain injury.

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“…Clinicians are typically asked during the first few days following cardiac arrest to monitor for seizures and offer a prognosis, i.e., determine the probability that the patient will have a poor outcome or eventually recover neurological function. Many abnormal EEG patterns seen in these patients do not meet criteria for electrographic seizures, but they may lay in the ictal interictal continuum and may require specific management guided by the EEG data (4). A poor prognosis prediction typically leads to the withdrawal of life sustaining therapies and death (5).…”

Section: Introductionmentioning

confidence: 99%

The International Cardiac Arrest Research (I-CARE) Consortium Electroencephalography Database

Amorim,

Zheng,

Ghassemi

et al. 2023

Preprint

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ObjectiveTo develop a harmonized multicenter clinical and electroencephalography (EEG) database for acute hypoxic-ischemic brain injury research involving patients with cardiac arrest.DesignMulticenter cohort, partly prospective and partly retrospective.SettingSeven academic or teaching hospitals from the U.S. and Europe.PatientsIndividuals aged 16 or older who were comatose after return of spontaneous circulation following a cardiac arrest who had continuous EEG monitoring were included.Interventionsnot applicable.Measurements and Main ResultsClinical and EEG data were harmonized and stored in a common Waveform Database (WFDB)-compatible format. Automated spike frequency, background continuity, and artifact detection on EEG were calculated with 10 second resolution and summarized hourly. Neurological outcome was determined at 3-6 months using the best Cerebral Performance Category (CPC) scale. This database includes clinical and 56,676 hours (3.9 TB) of continuous EEG data for 1,020 patients. Most patients died (N=603, 59%), 48 (5%) had severe neurological disability (CPC 3 or 4), and 369 (36%) had good functional recovery (CPC 1-2). There is significant variability in mean EEG recording duration depending on the neurological outcome (range 53-102h for CPC 1 and CPC 4, respectively). Epileptiform activity averaging 1 Hz or more in frequency for at least one hour was seen in 258 (25%) patients (19% for CPC 1-2 and 29% for CPC 3-5). Burst suppression was observed for at least one hour in 207 (56%) and 635 (97%) patients with CPC 1-2 and CPC 3-5, respectively.ConclusionsThe International Cardiac Arrest Research (I-CARE) consortium database provides a comprehensive real-world clinical and EEG dataset for neurophysiology research of comatose patients after cardiac arrest. This dataset covers the spectrum of abnormal EEG patterns after cardiac arrest, including epileptiform patterns and those in the ictal-interictal continuum.

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A matter of timing: EEG monitoring for neurological prognostication after cardiac arrest in the era of targeted temperature management

Cited by 7 publications

References 57 publications

A year in review in Minerva Anestesiologica 2019. Critical care

A year in review in Minerva Anestesiologica 2019. Critical care

Neurophysiology State Dynamics Underlying Acute Neurologic Recovery After Cardiac Arrest

The International Cardiac Arrest Research (I-CARE) Consortium Electroencephalography Database

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