Automated Pupillometry for Prediction of Electroencephalographic Reactivity in Critically Ill Patients: A Prospective Cohort Study.

EEG autonomic dysfunction brain injury encephalopathy intensive care unit pupillary function

Journal

Frontiers in neurology
ISSN: 1664-2295
Titre abrégé: Front Neurol
Pays: Switzerland
ID NLM: 101546899

Informations de publication

Date de publication:
2022
Historique:
received: 01 02 2022
accepted: 28 02 2022
entrez: 7 4 2022
pubmed: 8 4 2022
medline: 8 4 2022
Statut: epublish

Résumé

Electroencephalography (EEG) is widely used to monitor critically ill patients. However, EEG interpretation requires the presence of an experienced neurophysiologist and is time-consuming. Aim of this study was to evaluate whether parameters derived from an automated pupillometer (AP) might help to assess the degree of cerebral dysfunction in critically ill patients. Prospective study conducted in the Department of Intensive Care of Erasme University Hospital in Brussels, Belgium. Pupillary assessments were performed using the AP in three subgroups of patients, concomitantly monitored with continuous EEG: "anoxic brain injury", "Non-anoxic brain injury" and "other diseases". An independent neurologist blinded to patient's history and AP results scored the degree of encephalopathy and reactivity on EEG using a standardized scale. The mean value of Neurologic Pupil Index (NPi), pupillary size, constriction rate, constriction and dilation velocity (CV and DV) and latency for both eyes, obtained using the NPi®-200 (Neuroptics, Laguna Hills, CA, USA), were reported. We included 214 patients (mean age 60 years, 55% male). EEG tracings were categorized as: mild ( This study suggests that low DV measured by the AP might effectively identify an unreactive EEG background, in particular in critically ill patients without anoxic brain injury.

Sections du résumé

Background UNASSIGNED
Electroencephalography (EEG) is widely used to monitor critically ill patients. However, EEG interpretation requires the presence of an experienced neurophysiologist and is time-consuming. Aim of this study was to evaluate whether parameters derived from an automated pupillometer (AP) might help to assess the degree of cerebral dysfunction in critically ill patients.
Methods UNASSIGNED
Prospective study conducted in the Department of Intensive Care of Erasme University Hospital in Brussels, Belgium. Pupillary assessments were performed using the AP in three subgroups of patients, concomitantly monitored with continuous EEG: "anoxic brain injury", "Non-anoxic brain injury" and "other diseases". An independent neurologist blinded to patient's history and AP results scored the degree of encephalopathy and reactivity on EEG using a standardized scale. The mean value of Neurologic Pupil Index (NPi), pupillary size, constriction rate, constriction and dilation velocity (CV and DV) and latency for both eyes, obtained using the NPi®-200 (Neuroptics, Laguna Hills, CA, USA), were reported.
Results UNASSIGNED
We included 214 patients (mean age 60 years, 55% male). EEG tracings were categorized as: mild (
Conclusions UNASSIGNED
This study suggests that low DV measured by the AP might effectively identify an unreactive EEG background, in particular in critically ill patients without anoxic brain injury.

Identifiants

pubmed: 35386412
doi: 10.3389/fneur.2022.867603
pmc: PMC8977520
doi:

Types de publication

Journal Article

Langues

eng

Pagination

867603

Informations de copyright

Copyright © 2022 Peluso, Ferlini, Talamonti, Ndieugnou Djangang, Gouvea Bogossian, Menozzi, Annoni, Macchini, Legros, Severgnini, Creteur, Oddo, Vincent, Gaspard and Taccone.

Déclaration de conflit d'intérêts

FT and MO are scientific advisors for NeurOptics Inc. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Auteurs

Lorenzo Peluso (L)

Department of Intensive Care, Erasme University Hospital, Brussels, Belgium.

Lorenzo Ferlini (L)

Department of Neurology, Erasme University Hospital, Brussels, Belgium.

Marta Talamonti (M)

Department of Intensive Care, Erasme University Hospital, Brussels, Belgium.

Narcisse Ndieugnou Djangang (N)

Department of Intensive Care, Erasme University Hospital, Brussels, Belgium.

Elisa Gouvea Bogossian (E)

Department of Intensive Care, Erasme University Hospital, Brussels, Belgium.

Marco Menozzi (M)

Department of Intensive Care, Erasme University Hospital, Brussels, Belgium.

Filippo Annoni (F)

Department of Intensive Care, Erasme University Hospital, Brussels, Belgium.

Elisabetta Macchini (E)

Department of Intensive Care, Erasme University Hospital, Brussels, Belgium.

Benjamin Legros (B)

Department of Neurology, Erasme University Hospital, Brussels, Belgium.

Paolo Severgnini (P)

Department of Biotechnology and Life Sciences, Insubria University, Cardiac Anesthesiology and Intensive Care - ASST Sette Laghi, Varese, Italy.

Jacques Creteur (J)

Department of Intensive Care, Erasme University Hospital, Brussels, Belgium.

Mauro Oddo (M)

Critical Care Clinical Research Unit, Department of Intensive Care Medicine, CHUV-Lausanne University Hospital, Lausanne, Switzerland.

Jean-Louis Vincent (JL)

Department of Intensive Care, Erasme University Hospital, Brussels, Belgium.

Nicolas Gaspard (N)

Department of Neurology, Erasme University Hospital, Brussels, Belgium.
Department of Neurology, Yale University Medical School, New Haven, CT, United States.

Fabio Silvio Taccone (FS)

Department of Intensive Care, Erasme University Hospital, Brussels, Belgium.

Classifications MeSH