Abstract

About 80% of patients resuscitated from CA are comatose at ICU admission and nearly 50% of survivors are still unawake at 72 h. Predicting neurological outcome of these patients is important to provide correct information to patient’s relatives, avoid disproportionate care in patients with irreversible hypoxic–ischemic brain injury (HIBI) and inappropriate withdrawal of care in patients with a possible favorable neurological recovery. ERC/ESICM 2021 algorithm allows a classification as “poor outcome likely” in 32%, the outcome remaining “indeterminate” in 68%. The crucial question is to know how we could improve the assessment of both unfavorable but also favorable outcome prediction. Neurophysiological tests, i.e., electroencephalography (EEG) and evoked-potentials (EPs) are a non-invasive bedside investigations. The EEG is the record of brain electrical fields, characterized by a high temporal resolution but a low spatial resolution. EEG is largely available, and represented the most widely tool use in recent survey examining current neuro-prognostication practices. The severity of HIBI is correlated with the predominant frequency and background continuity of EEG leading to “highly malignant” patterns as suppression or burst suppression in the most severe HIBI. EPs differ from EEG signals as they are stimulus induced and represent the summated activities of large populations of neurons firing in synchrony, requiring the average of numerous stimulations. Different EPs (i.e., somato sensory EPs (SSEPs), brainstem auditory EPs (BAEPs), middle latency auditory EPs (MLAEPs) and long latency event-related potentials (ERPs) with mismatch negativity (MMN) and P300 responses) can be assessed in ICU, with different brain generators and prognostic values. In the present review, we summarize EEG and EPs signal generators, recording modalities, interpretation and prognostic values of these different neurophysiological tools. Finally, we assess the perspective for futures neurophysiological investigations, aiming to reduce prognostic uncertainty in comatose and disorders of consciousness (DoC) patients after CA.

Details

Title
Prognostication after cardiac arrest: how EEG and evoked potentials may improve the challenge
Author
Benghanem, Sarah 1 ; Pruvost-Robieux, Estelle 2 ; Bouchereau, Eléonore 3 ; Gavaret, Martine 2 ; Cariou, Alain 4 

 Cochin Hospital, Assistance Publique – Hôpitaux de Paris (AP-HP), Medical ICU, Paris, France (GRID:grid.411784.f) (ISNI:0000 0001 0274 3893); University Paris Cité, Medical School, Paris, France (GRID:grid.508487.6) (ISNI:0000 0004 7885 7602); After ROSC Network, Paris, France (GRID:grid.508487.6); INSERM FHU NeuroVascNeurosciences de Paris-IPNP, UMR 1266, Institut de Psychiatrie et, Paris, France (GRID:grid.7429.8) (ISNI:0000000121866389) 
 University Paris Cité, Medical School, Paris, France (GRID:grid.508487.6) (ISNI:0000 0004 7885 7602); GHU Psychiatry and Neurosciences, Neurophysiology and Epileptology Department, Paris, France (GRID:grid.508487.6); INSERM FHU NeuroVascNeurosciences de Paris-IPNP, UMR 1266, Institut de Psychiatrie et, Paris, France (GRID:grid.7429.8) (ISNI:0000000121866389) 
 G.H.U Paris Psychiatry and Neurosciences, Department of Neurocritical Care, Paris, France (GRID:grid.7429.8); INSERM FHU NeuroVascNeurosciences de Paris-IPNP, UMR 1266, Institut de Psychiatrie et, Paris, France (GRID:grid.7429.8) (ISNI:0000000121866389) 
 Cochin Hospital, Assistance Publique – Hôpitaux de Paris (AP-HP), Medical ICU, Paris, France (GRID:grid.411784.f) (ISNI:0000 0001 0274 3893); University Paris Cité, Medical School, Paris, France (GRID:grid.508487.6) (ISNI:0000 0004 7885 7602); After ROSC Network, Paris, France (GRID:grid.508487.6); Paris-Cardiovascular-Research-Center (Sudden-Death-Expertise-Center), INSERM U970, Paris, France (GRID:grid.462416.3) (ISNI:0000 0004 0495 1460) 
Publication year
2022
Publication date
Dec 2022
Publisher
Springer Nature B.V.
e-ISSN
21105820
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2748041852
Copyright
© The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.