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

Details

Serval ID
serval:BIB_A1BDFA607124
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Automated Pupillometry for Prediction of Electroencephalographic Reactivity in Critically Ill Patients: A Prospective Cohort Study.
Journal
Frontiers in neurology
Author(s)
Peluso L., Ferlini L., Talamonti M., Ndieugnou Djangang N., Gouvea Bogossian E., Menozzi M., Annoni F., Macchini E., Legros B., Severgnini P., Creteur J., Oddo M., Vincent J.L., Gaspard N., Taccone F.S.
ISSN
1664-2295 (Print)
ISSN-L
1664-2295
Publication state
Published
Issued date
2022
Peer-reviewed
Oui
Volume
13
Pages
867603
Language
english
Notes
Publication types: Journal Article
Publication Status: epublish
Abstract
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 (n = 111, 52%), moderate (n = 65, 30%) or severe (n = 16, 8%) encephalopathy; burst-suppression (n = 19, 9%) or suppression background (n = 3, 1%); a total of 38 (18%) EEG were classified as "unreactive". We found a significant difference in all pupillometry variables among different EEG categories. Moreover, an unreactive EEG was associated with lower NPi, pupil size, pupillary reactivity, CV and DV and a higher latency than reactive recordings. Low DV (Odds ratio 0.020 [95% confidence intervals 0.002-0.163]; p < 0.01) was independently associated with an unreactive EEG, together with the use of analgesic/sedative drugs and high lactate concentrations. In particular, DV values had an area under the curve (AUC) of 0.86 [0.79-0.92; p < 0.01] to predict the presence of unreactive EEG. In subgroups analyses, AUC of DV to predict unreactive EEG was lower (0.72 [0.56-0.87]; p < 0.01) in anoxic brain injury than Non-anoxic brain injury (0.92 [0.85-1.00]; p < 0.01) and other diseases (0.96 [0.90-1.00]; p < 0.01).
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.
Keywords
EEG, autonomic dysfunction, brain injury, encephalopathy, intensive care unit, pupillary function
Pubmed
Web of science
Open Access
Yes
Create date
25/04/2022 13:20
Last modification date
21/11/2023 8:11
Usage data