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Delirium detection by a novel bispectral electroencephalography device in general hospital
Author(s) -
Shinozaki Gen,
Chan Aubrey C.,
Sparr Nicholas A,
Zarei Kasra,
Gaul Lindsey N.,
Heinzman Jonathan T.,
Robles Julian,
Yuki Kumi,
Chronis Theodosis J.,
Ando Timothy,
Wong Terrence,
Sabbagh Sayeh,
Weckmann Michelle T.,
Lee Sangil,
Yamada Thoru,
Karam Matthew D.,
Noiseux Nicolas O.,
Shinozaki Eri,
Cromwell John W.
Publication year - 2018
Publication title -
psychiatry and clinical neurosciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.609
H-Index - 74
eISSN - 1440-1819
pISSN - 1323-1316
DOI - 10.1111/pcn.12783
Subject(s) - delirium , electroencephalography , medicine , intensive care unit , confusion , bispectral index , rating scale , emergency medicine , intensive care medicine , anesthesia , psychology , psychiatry , sedation , psychoanalysis , developmental psychology
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.