Journal article
Identification of Patients With High Mortality Risk and Prediction of Outcomes in Delirium by Bispectral EEG
The journal of clinical psychiatry, Vol.80(5), 19m12749
09/03/2019
DOI: 10.4088/JCP.19m12749
PMCID: PMC7181374
PMID: 31483958
Abstract
Delirium is common and dangerous, yet underdetected and undertreated. Current screening questionnaires are subjective and ineffectively implemented in busy hospital workflows. Electroencephalography (EEG) can objectively detect the diffuse slowing characteristic of delirium, but it is not suitable for high-throughput screening due to size, cost, and the expertise required for lead placement and interpretation. This study hypothesized that an efficient and reliable point-of-care EEG device for high-throughput screening could be developed.
This prospective study, which measured bispectral EEG (BSEEG) from elderly inpatients to assess their outcomes, was conducted at the University of Iowa Hospitals and Clinics from January 2016 to October 2017. A BSEEG score was defined based on the distribution of 2,938 EEG recordings from the 428 subjects who were assessed for delirium; primary outcomes measured were hospital length of stay, discharge disposition, and mortality.
A total of 274 patients had BSEEG score data available for analysis. Delirium and BSEEG score had a significant association (P < .001). Higher BSEEG scores were significantly correlated with length of stay (P < .001 unadjusted, P = .001 adjusted for age, sex, and Charlson Comorbidity Index [CCI] score) as well as with discharge not to home (P < .01). Hazard ratio for survival controlling for age, sex, CCI score, and delirium status was 1.35 (95% CI,1.04 to 1.76; P = .025).
In BSEEG, an efficient and reliable device that provides an objective measurement of delirium status was developed. The BSEEG score is significantly associated with pertinent clinical outcomes of mortality, hospital length of stay, and discharge disposition. The BSEEG score better predicts mortality than does clinical delirium status. This study identified a previously unrecognized subpopulation of patients without clinical features of delirium who are at increased mortality risk.
Details
- Title: Subtitle
- Identification of Patients With High Mortality Risk and Prediction of Outcomes in Delirium by Bispectral EEG
- Creators
- Gen Shinozaki - Interdisciplinary Graduate Program for Neuroscience, University of Iowa, Iowa City, Iowa, USANicholas L Bormann - Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, Iowa, USAAubrey C Chan - Department of Internal Medicine, University of Iowa Carver College of Medicine, Iowa City, Iowa, USAKasra Zarei - Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, Iowa, USANicholas A Sparr - Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, Iowa, USAMason J Klisares - Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, Iowa, USASydney S Jellison - Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, Iowa, USAJonathan T Heinzman - Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, Iowa, USAElijah B Dahlstrom - Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, Iowa, USAGabrielle N Duncan - Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, Iowa, USALindsey N Gaul - Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, Iowa, USARobert J Wanzek - Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, Iowa, USAEllyn M Cramer - Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, Iowa, USACharlotte G Wimmel - Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, Iowa, USASayeh Sabbagh - Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, Iowa, USAKumi Yuki - Department of Family Medicine, University of Iowa Carver College of Medicine, Iowa City, Iowa, USAMichelle T Weckmann - Department of Family Medicine, University of Iowa Carver College of Medicine, Iowa City, Iowa, USAThoru Yamada - Department of Neurology, University of Iowa Carver College of Medicine, Iowa City, Iowa, USAMatthew D Karam - Department of Orthopedic Surgery, University of Iowa Carver College of Medicine, Iowa City, Iowa, USANicolas O Noiseux - Department of Orthopedic Surgery, University of Iowa Carver College of Medicine, Iowa City, Iowa, USAEri Shinozaki - Department of Internal Medicine, University of Iowa Carver College of Medicine, Iowa City, Iowa, USAHyunkeun R Cho - College of Public Health, University of Iowa, Iowa City, Iowa, USASangil Lee - Department of Emergency Medicine, University of Iowa Carver College of Medicine, Iowa City, Iowa, USAJohn W Cromwell - Department of Surgery, University of Iowa Carver College of Medicine, Iowa City, Iowa, USA
- Resource Type
- Journal article
- Publication Details
- The journal of clinical psychiatry, Vol.80(5), 19m12749
- DOI
- 10.4088/JCP.19m12749
- PMID
- 31483958
- PMCID
- PMC7181374
- NLM abbreviation
- J Clin Psychiatry
- ISSN
- 0160-6689
- eISSN
- 1555-2101
- Publisher
- United States
- Grant note
- T35 HL007485 / NHLBI NIH HHS T32 MH019113 / NIMH NIH HHS
- Language
- English
- Date published
- 09/03/2019
- Academic Unit
- Neurology; Psychiatry; Biostatistics; Surgery; Family and Community Medicine; Anesthesia; Injury Prevention Research Center; Otolaryngology; Emergency Medicine; Iowa Neuroscience Institute; Orthopedics and Rehabilitation; General Internal Medicine; Neurosurgery; Internal Medicine
- Record Identifier
- 9984070820102771
Metrics
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