Neurophysiology State Dynamics Underlying Acute Neurologic Recovery After Cardiac Arrest

Overview

Journal Neurology

Specialty Neurology

Date 2023 Jul 6

PMID 37414565

Authors

Edilberto Amorim

Wei-Long Zheng

Jin Jing

Mohammad M Ghassemi

Jong Woo Lee

Ona Wu

Susan T Herman

Trudy Pang

Adithya Sivaraju

Nicolas Gaspard

Lawrence Hirsch

Barry J Ruijter

Marleen C Tjepkema-Cloostermans

Jeannette Hofmeijer

Michel J A M van Putten

M Brandon Westover

Affiliations

Soon will be listed here.

Abstract

Background And Objectives: Epileptiform activity and burst suppression are neurophysiology signatures reflective of severe brain injury after cardiac arrest. We aimed to delineate the evolution of coma neurophysiology feature ensembles associated with recovery from coma after cardiac arrest.

Methods: Adults in acute coma after cardiac arrest were included in a retrospective database involving 7 hospitals. The combination of 3 quantitative EEG features (burst suppression ratio [BSup], spike frequency [SpF], and Shannon entropy [En]) was used to define 5 distinct neurophysiology states: epileptiform high entropy (EHE: SpF ≥4 per minute and En ≥5); epileptiform low entropy (ELE: SpF ≥4 per minute and <5 En); nonepileptiform high entropy (NEHE: SpF <4 per minute and ≥5 En); nonepileptiform low entropy (NELE: SpF <4 per minute and <5 En), and burst suppression (BSup ≥50% and SpF <4 per minute). State transitions were measured at consecutive 6-hour blocks between 6 and 84 hours after return of spontaneous circulation. Good neurologic outcome was defined as best cerebral performance category 1-2 at 3-6 months.

Results: One thousand thirty-eight individuals were included (50,224 hours of EEG), and 373 (36%) had good outcome. Individuals with EHE state had a 29% rate of good outcome, while those with ELE had 11%. Transitions out of an EHE or BSup state to an NEHE state were associated with good outcome (45% and 20%, respectively). No individuals with ELE state lasting >15 hours had good recovery.

Discussion: Transition to high entropy states is associated with an increased likelihood of good outcome despite preceding epileptiform or burst suppression states. High entropy may reflect mechanisms of resilience to hypoxic-ischemic brain injury.

Citing Articles

Using artificial intelligence to optimize anti-seizure treatment and EEG-guided decisions in severe brain injury.

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PMID: 39855915 PMC: 11840355. DOI: 10.1016/j.neurot.2025.e00524.

Early Burst Suppression Similarity Association with Structural Brain Injury Severity on MRI After Cardiac Arrest.

Shivdat S, Zhan T, De Palma A, Zheng W, Krishnamurthy P, Paneerselvam E Neurocrit Care. 2024; 42(1):175-184.

PMID: 39043984 PMC: 11757804. DOI: 10.1007/s12028-024-02047-6.

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