1. Delirium detection by a novel bispectral electroencephalography device in general hospital
- Author
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Kasra Zarei, Jonathan T. Heinzman, Aubrey C. Chan, Michelle T. Weckmann, Matthew D. Karam, Kumi Yuki, Lindsey N. Gaul, Theodosis J. Chronis, Gen Shinozaki, John W. Cromwell, Eri Shinozaki, Julian Robles, Thoru Yamada, Sayeh Sabbagh, Nicolas O. Noiseux, Nicholas A Sparr, Sangil Lee, Timothy Ando, and Terrence Wong
- Subjects
Male ,medicine.medical_specialty ,Point-of-Care Systems ,Pilot Projects ,Electroencephalography ,behavioral disciplines and activities ,Article ,law.invention ,03 medical and health sciences ,0302 clinical medicine ,Rating scale ,law ,mental disorders ,medicine ,Humans ,Mass Screening ,030212 general & internal medicine ,General hospital ,Mass screening ,Aged ,Point of care ,Aged, 80 and over ,medicine.diagnostic_test ,business.industry ,General Neuroscience ,Brain ,Delirium ,General Medicine ,Middle Aged ,Intensive care unit ,Psychiatry and Mental health ,Neurology ,Emergency medicine ,Assessment methods ,Female ,Neurology (clinical) ,medicine.symptom ,business ,030217 neurology & neurosurgery - 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.
- Published
- 2018
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