Pain anticipation is a new behavioural sign of minimally conscious state.

EEG disorder of consciousness intensive care pain anticipation trace conditioning

Journal

Brain communications
ISSN: 2632-1297
Titre abrégé: Brain Commun
Pays: England
ID NLM: 101755125

Informations de publication

Date de publication:
2024
Historique:
received: 20 11 2023
revised: 26 07 2024
accepted: 12 09 2024
medline: 30 9 2024
pubmed: 30 9 2024
entrez: 30 9 2024
Statut: epublish

Résumé

Probing cognition and consciousness in the absence of functional communication remains an extremely challenging task. In this perspective, we imagined a basic clinical procedure to explore pain anticipation at bedside. In a series of 61 patients with a disorder of consciousness, we tested the existence of a nociceptive anticipation response by pairing a somaesthetic stimulation with a noxious stimulation. We then explored how nociceptive anticipation response correlated with (i) clinical status inferred from Coma Recovery Scale-Revised scoring, (ii) with an EEG signature of stimulus anticipation-the contingent negative variation-and (iii) how nociceptive anticipation response could predict consciousness outcome at 6 months. Proportion of nociceptive anticipation response differed significantly according to the state of consciousness: nociceptive anticipation response was present in 5 of 5 emerging from minimally conscious state patients (100%), in 10 of 11 minimally conscious state plus patients (91%), but only in 8 of 17 minimally conscious state minus patients (47%), and only in 1 of 24 vegetative state/unresponsive wakefulness syndrome patients (4%) (

Identifiants

pubmed: 39346020
doi: 10.1093/braincomms/fcae311
pii: fcae311
pmc: PMC11430917
doi:

Types de publication

Journal Article

Langues

eng

Pagination

fcae311

Informations de copyright

© The Author(s) 2024. Published by Oxford University Press on behalf of the Guarantors of Brain.

Déclaration de conflit d'intérêts

The authors report no competing interests.

Auteurs

Aude Sangare (A)

Paris Brain Institute-ICM, Inserm U1127, CNRS UMR 7225, PICNIC Lab, Sorbonne Universite, Paris 75013, France.
Département de Neurophysiologie, Sorbonne Université, Assistance Publique-Hôpitaux de Paris, Groupe Hospitalier Pitié-Salpêtrière Charles Foix, Paris 75013, France.

Esteban Munoz-Musat (E)

Paris Brain Institute-ICM, Inserm U1127, CNRS UMR 7225, PICNIC Lab, Sorbonne Universite, Paris 75013, France.

Amina Ben Salah (A)

Paris Brain Institute-ICM, Inserm U1127, CNRS UMR 7225, PICNIC Lab, Sorbonne Universite, Paris 75013, France.

Melanie Valente (M)

Paris Brain Institute-ICM, Inserm U1127, CNRS UMR 7225, PICNIC Lab, Sorbonne Universite, Paris 75013, France.
Département de Neurophysiologie, Sorbonne Université, Assistance Publique-Hôpitaux de Paris, Groupe Hospitalier Pitié-Salpêtrière Charles Foix, Paris 75013, France.

Clemence Marois (C)

Département de Neurologie, Sorbonne Université, Assistance Publique-Hôpitaux de Paris, Groupe Hospitalier Pitié-Salpêtrière Charles Foix, médecine intensive et réanimation Paris, Paris 75013, France.

Sophie Demeret (S)

Département de Neurologie, Sorbonne Université, Assistance Publique-Hôpitaux de Paris, Groupe Hospitalier Pitié-Salpêtrière Charles Foix, médecine intensive et réanimation Paris, Paris 75013, France.

Jacobo Diego Sitt (JD)

Paris Brain Institute-ICM, Inserm U1127, CNRS UMR 7225, PICNIC Lab, Sorbonne Universite, Paris 75013, France.

Benjamin Rohaut (B)

Paris Brain Institute-ICM, Inserm U1127, CNRS UMR 7225, PICNIC Lab, Sorbonne Universite, Paris 75013, France.
Département de Neurologie, Sorbonne Université, Assistance Publique-Hôpitaux de Paris, Groupe Hospitalier Pitié-Salpêtrière Charles Foix, médecine intensive et réanimation Paris, Paris 75013, France.

Lionel Naccache (L)

Paris Brain Institute-ICM, Inserm U1127, CNRS UMR 7225, PICNIC Lab, Sorbonne Universite, Paris 75013, France.
Département de Neurophysiologie, Sorbonne Université, Assistance Publique-Hôpitaux de Paris, Groupe Hospitalier Pitié-Salpêtrière Charles Foix, Paris 75013, France.

Classifications MeSH