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Psychiatry Clin Neurosci. 2018 Dec;72(12):856-863. doi: 10.1111/pcn.12783. Epub 2018 Oct 25.

Delirium detection by a novel bispectral electroencephalography device in general hospital.

Author information

1
Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, USA.
2
Department of Internal Medicine, University of Iowa Carver College of Medicine, Iowa City, USA.
3
Department of Family Medicine, University of Iowa Carver College of Medicine, Iowa City, USA.
4
Department of Psychiatry, Stanford University School of Medicine, Stanford, USA.
5
Department of Internal Medicine, Highland Hospital, Alameda Health System, Oakland, USA.
6
Department of Emergency Medicine, University of Iowa Carver College of Medicine, Iowa City, USA.
7
Department of Neurology, University of Iowa Carver College of Medicine, Iowa City, USA.
8
Department of Orthopedics and Rehabilitation, University of Iowa Carver College of Medicine, Iowa City, USA.
9
Department of Surgery, University of Iowa Carver College of Medicine, Iowa City, USA.

Abstract

AIM:

Delirium is common and dangerous among elderly inpatients; yet, it is underdiagnosed and thus undertreated. This study aimed to test the diagnostic characteristics of a noninvasive point-of-care device with two-channel (bispectral) electroencephalography (EEG) for the screening of delirium in the hospital.

METHODS:

Patients admitted to the University of Iowa Hospitals and Clinics were assessed for the presence of delirium with a clinical assessment, the Confusion Assessment Method for Intensive Care Unit and Delirium Rating Scale. Subsequently, we obtained a 10-min bispectral EEG (BSEEG) recording from a hand-held electroencephalogram device during hospitalization. We performed power spectral density analysis to differentiate between those patients with and without delirium.

RESULTS:

Initially 45 subjects were used as a test dataset to establish a cut-off. The BSEEG index was determined to be a significant indicator of delirium, with sensitivity 80% and specificity 87.7%. An additional independent validation dataset with 24 patients confirmed the validity of the approach, with a sensitivity of 83.3% and specificity of 83.3%.

CONCLUSION:

In this pilot study, the BSEEG method was able to distinguish delirious patients from non-delirious patients. Our data showed the feasibility of this technology for mass screening of delirium in the hospital.

KEYWORDS:

delirium; electroencephalogram; point of care; power spectral analysis

PMID:
30246448
PMCID:
PMC6317342
DOI:
10.1111/pcn.12783
[Indexed for MEDLINE]
Free PMC Article

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