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Evaluation of point-of-care thumb-size bispectral electroencephalography device to quantify delirium severity and predict mortality

Published online by Cambridge University Press:  02 August 2021

Takehiko Yamanashi
Affiliation:
Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Palo Alto, California, USA; and Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, Iowa, USA; and Department of Neuropsychiatry, Tottori University Faculty of Medicine, Yonago, Japan
Kaitlyn J. Crutchley
Affiliation:
Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, Iowa, USA; and School of Medicine, University of Nebraska Medical Center, Nebraska, USA
Nadia E. Wahba
Affiliation:
Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, Iowa, USA
Eleanor J. Sullivan
Affiliation:
Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, Iowa, USA
Katie R. Comp
Affiliation:
Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, Iowa, USA
Mari Kajitani
Affiliation:
Fujitsu Laboratories Ltd, Tokyo, Japan
Tammy Tran
Affiliation:
Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, Iowa, USA
Manisha V. Modukuri
Affiliation:
Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, Iowa, USA
Pedro S. Marra
Affiliation:
Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, Iowa, USA
Felipe M. Herrmann
Affiliation:
Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, Iowa, USA
Gloria Chang
Affiliation:
Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, Iowa, USA
Zoe-Ella M. Anderson
Affiliation:
Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, Iowa, USA
Masaaki Iwata
Affiliation:
Department of Neuropsychiatry, Tottori University Faculty of Medicine, Yonago, Japan
Ken Kobayashi
Affiliation:
Fujitsu Laboratories Ltd, Tokyo, Japan
Koichi Kaneko
Affiliation:
Department of Neuropsychiatry, Tottori University Faculty of Medicine, Yonago, Japan
Yuhei Umeda
Affiliation:
Fujitsu Laboratories Ltd, Tokyo, Japan
Yoshimasa Kadooka
Affiliation:
Fujitsu Ltd, Tokyo, Japan
Sangil Lee
Affiliation:
Department of Emergency Medicine, University of Iowa Carver College of Medicine, Iowa City, Iowa, USA
Eri Shinozaki
Affiliation:
Department of Internal Medicine, University of Iowa Carver College of Medicine, Iowa City, Iowa, USA
Matthew D. Karam
Affiliation:
Department of Orthopedic Surgery, University of Iowa Carver College of Medicine, Iowa City, Iowa, USA
Nicolas O. Noiseux
Affiliation:
Department of Orthopedic Surgery, University of Iowa Carver College of Medicine, Iowa City, Iowa, USA
Gen Shinozaki*
Affiliation:
Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Palo Alto, California, USA; and Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, Iowa, USA
*
Correspondence: Gen Shinozaki. Email: gens@stanford.edu

Abstract

Background

We have developed the bispectral electroencephalography (BSEEG) method for detection of delirium and prediction of poor outcomes.

Aims

To improve the BSEEG method by introducing a new EEG device.

Method

In a prospective cohort study, EEG data were obtained and BSEEG scores were calculated. BSEEG scores were filtered on the basis of standard deviation (s.d.) values to exclude signals with high noise. Both non-filtered and s.d.-filtered BSEEG scores were analysed. BSEEG scores were compared with the results of three delirium screening scales: the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU), the Delirium Rating Scale-Revised-98 (DRS) and the Delirium Observation Screening Scale (DOSS). Additionally, the 365-day mortalities and the length of stay (LOS) in the hospital were analysed.

Results

We enrolled 279 elderly participants and obtained 620 BSEEG recordings; 142 participants were categorised as BSEEG-positive, reflecting slower EEG activity. BSEEG scores were higher in the CAM-ICU-positive group than in the CAM-ICU-negative group. There were significant correlations between BSEEG scores and scores on the DRS and the DOSS. The mortality rate of the BSEEG-positive group was significantly higher than that of the BSEEG-negative group. The LOS of the BSEEG-positive group was longer compared with that of the BSEEG-negative group. BSEEG scores after s.d. filtering showed stronger correlations with delirium screening scores and more significant prediction of mortality.

Conclusions

We confirmed the usefulness of the BSEEG method for detection of delirium and of delirium severity, and prediction of patient outcomes with a new EEG device.

Type
Paper
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press on behalf of the Royal College of Psychiatrists

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