Topological data analysis (TDA) enhances bispectral EEG (BSEEG) algorithm for detection of delirium

Takehiko Yamanashi; Mari Kajitani; Masaaki Iwata; Kaitlyn J. Crutchley; Pedro Marra; Johnny R. Malicoat; Jessica C. Williams; Lydia R. Leyden; Hailey Long; Duachee Lo; Cassidy J. Schacher; Kazuaki Hiraoka; Tomoyuki Tsunoda; Ken Kobayashi; Yoshiaki Ikai; Koichi Kaneko; Yuhei Umeda; Yoshimasa Kadooka; Gen Shinozaki

doi:10.1038/s41598-020-79391-y

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Topological data analysis (TDA) enhances bispectral EEG (BSEEG) algorithm for detection of delirium

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Topological data analysis (TDA) enhances bispectral EEG (BSEEG) algorithm for detection of delirium

Takehiko Yamanashi, Mari Kajitani, Masaaki Iwata, Kaitlyn J. Crutchley, Pedro Marra, Johnny R. Malicoat, Jessica C. Williams, Lydia R. Leyden, Hailey Long, Duachee Lo, …

Scientific reports, Vol.11(1), 304

01/01/2021

DOI: 10.1038/s41598-020-79391-y

PMID: 33431928

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Abstract

Abstract Current methods for screening and detecting delirium are not practical in clinical settings. We previously showed that a simplified EEG with bispectral electroencephalography (BSEEG) algorithm can detect delirium in elderly inpatients. In this study, we performed a post-hoc BSEEG data analysis using larger sample size and performed topological data analysis to improve the BSEEG method. Data from 274 subjects included in the previous study were analyzed as a 1st cohort. Subjects were enrolled at the University of Iowa Hospitals and Clinics (UIHC) between January 30, 2016, and October 30, 2017. A second cohort with 265 subjects was recruited between January 16, 2019, and August 19, 2019. The BSEEG score was calculated as a power ratio between low frequency to high frequency using our newly developed algorithm. Additionally, Topological data analysis (TDA) score was calculated by applying TDA to our EEG data. The BSEEG score and TDA score were compared between those patients with delirium and without delirium. Among the 274 subjects from the first cohort, 102 were categorized as delirious. Among the 206 subjects from the second cohort, 42 were categorized as delirious. The areas under the curve (AUCs) based on BSEEG score were 0.72 (1st cohort, Fp1-A1), 0.76 (1st cohort, Fp2-A2), and 0.67 (2nd cohort). AUCs from TDA were much higher at 0.82 (1st cohort, Fp1-A1), 0.84 (1st cohort, Fp2-A2), and 0.78 (2nd cohort). When sensitivity was set to be 0.80, the TDA drastically improved specificity to 0.66 (1st cohort, Fp1-A1), 0.72 (1st cohort, Fp2-A2), and 0.62 (2nd cohort), compared to 0.48 (1st cohort, Fp1-A1), 0.54 (1st cohort, Fp2-A2), and 0.46 (2nd cohort) with BSEEG. BSEEG has the potential to detect delirium, and TDA is helpful to improve the performance.

Details

Title: Subtitle: Topological data analysis (TDA) enhances bispectral EEG (BSEEG) algorithm for detection of delirium
Creators: Takehiko Yamanashi - Department of Psychiatry, University of Iowa Carver College of Medicine
Mari Kajitani - FUJITSU LABORATORIES LTD
Masaaki Iwata - Department of Neuropsychiatry, Faculty of Medicine, Tottori University
Kaitlyn J. Crutchley - Department of Psychiatry, University of Iowa Carver College of Medicine
Pedro Marra - Department of Psychiatry, University of Iowa Carver College of Medicine
Johnny R. Malicoat - Department of Psychiatry, University of Iowa Carver College of Medicine
Jessica C. Williams - Department of Psychiatry, University of Iowa Carver College of Medicine
Lydia R. Leyden - Department of Psychiatry, University of Iowa Carver College of Medicine
Hailey Long - Department of Psychiatry, University of Iowa Carver College of Medicine
Duachee Lo - Department of Psychiatry, University of Iowa Carver College of Medicine
Cassidy J. Schacher - Department of Psychiatry, University of Iowa Carver College of Medicine
Kazuaki Hiraoka - FUJITSU LABORATORIES LTD
Tomoyuki Tsunoda - FUJITSU LABORATORIES LTD
Ken Kobayashi - FUJITSU LABORATORIES LTD
Yoshiaki Ikai - FUJITSU LABORATORIES LTD
Koichi Kaneko - Department of Neuropsychiatry, Faculty of Medicine, Tottori University
Yuhei Umeda - FUJITSU LABORATORIES LTD
Yoshimasa Kadooka - FUJITSU LTD
Gen Shinozaki - Department of Psychiatry, University of Iowa Carver College of Medicine
Resource Type: Journal article
Publication Details: Scientific reports, Vol.11(1), 304
DOI: 10.1038/s41598-020-79391-y
PMID: 33431928
NLM abbreviation: Sci Rep
ISSN: 2045-2322
eISSN: 2045-2322
Publisher: Nature Publishing Group
Grant note: name: National Science Foundation, award: 1664364; name: Fujitsu Laboratories LTD
Language: English
Date published: 01/01/2021
Academic Unit: Psychiatry; Microbiology and Immunology; Psychological and Brain Sciences; Iowa Neuroscience Institute; Anesthesia; Neurosurgery
Record Identifier: 9984070701602771

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