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

Delirium bispectral EEG (BSEEG) delirium rating scales electroencephalography mortality

Journal

The British journal of psychiatry : the journal of mental science
ISSN: 1472-1465
Titre abrégé: Br J Psychiatry
Pays: England
ID NLM: 0342367

Informations de publication

Date de publication:
02 Aug 2021
Historique:
entrez: 20 1 2022
pubmed: 21 1 2022
medline: 21 1 2022
Statut: aheadofprint

Résumé

We have developed the bispectral electroencephalography (BSEEG) method for detection of delirium and prediction of poor outcomes. To improve the BSEEG method by introducing a new EEG device. 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. 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. 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.

Sections du résumé

BACKGROUND BACKGROUND
We have developed the bispectral electroencephalography (BSEEG) method for detection of delirium and prediction of poor outcomes.
AIMS OBJECTIVE
To improve the BSEEG method by introducing a new EEG device.
METHOD METHODS
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 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 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.

Identifiants

pubmed: 35049468
doi: 10.1192/bjp.2021.101
pii: S000712502100101X
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1-8

Subventions

Organisme : Fujitsu Laboratories LTD

Auteurs

Takehiko Yamanashi (T)

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 (KJ)

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 (NE)

Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, Iowa,USA.

Eleanor J Sullivan (EJ)

Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, Iowa,USA.

Katie R Comp (KR)

Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, Iowa,USA.

Mari Kajitani (M)

Fujitsu Laboratories Ltd, Tokyo, Japan.

Tammy Tran (T)

Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, Iowa,USA.

Manisha V Modukuri (MV)

Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, Iowa,USA.

Pedro S Marra (PS)

Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, Iowa,USA.

Felipe M Herrmann (FM)

Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, Iowa,USA.

Gloria Chang (G)

Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, Iowa,USA.

Zoe-Ella M Anderson (ZM)

Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, Iowa,USA.

Masaaki Iwata (M)

Department of Neuropsychiatry, Tottori University Faculty of Medicine, Yonago, Japan.

Ken Kobayashi (K)

Fujitsu Laboratories Ltd, Tokyo, Japan.

Koichi Kaneko (K)

Department of Neuropsychiatry, Tottori University Faculty of Medicine, Yonago, Japan.

Yuhei Umeda (Y)

Fujitsu Laboratories Ltd, Tokyo, Japan.

Yoshimasa Kadooka (Y)

Fujitsu Ltd, Tokyo, Japan.

Sangil Lee (S)

Department of Emergency Medicine, University of Iowa Carver College of Medicine, Iowa City, Iowa, USA.

Eri Shinozaki (E)

Department of Internal Medicine, University of Iowa Carver College of Medicine, Iowa City, Iowa, USA.

Matthew D Karam (MD)

Department of Orthopedic Surgery, University of Iowa Carver College of Medicine, Iowa City, Iowa, USA.

Nicolas O Noiseux (NO)

Department of Orthopedic Surgery, University of Iowa Carver College of Medicine, Iowa City, Iowa, USA.

Gen Shinozaki (G)

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.

Classifications MeSH