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Automatic continuous EEG signal analysis for diagnosis of delirium in patients with sepsis

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@article{2cc536683d894af99a120fb0b35e4b52,
title = "Automatic continuous EEG signal analysis for diagnosis of delirium in patients with sepsis",
abstract = "OBJECTIVE: In critical care, continuous EEG (cEEG) monitoring is useful for delirium diagnosis. Although visual cEEG analysis is most commonly used, automatic cEEG analysis has shown promising results in small samples. Here we aimed to compare visual versus automatic cEEG analysis for delirium diagnosis in septic patients.METHODS: We obtained cEEG recordings from 102 septic patients who were scored for delirium six times daily. A total of 1252 cEEG blocks were visually analyzed, of which 805 blocks were also automatically analyzed.RESULTS: Automatic cEEG analyses revealed that delirium was associated with 1) high mean global field power (p < 0.005), mainly driven by delta activity; 2) low average coherence across all electrode pairs and all frequencies (p < 0.01); 3) lack of intrahemispheric (fronto-temporal and temporo-occipital regions) and interhemispheric coherence (p < 0.05); and 4) lack of cEEG reactivity (p < 0.005). Classification accuracy was assessed by receiver operating characteristic (ROC) curve analysis, revealing a slightly higher area under the curve for visual analysis (0.88) than automatic analysis (0.74) (p < 0.05).CONCLUSIONS: Automatic cEEG analysis is a useful supplement to visual analysis, and provides additional cEEG diagnostic classifiers.SIGNIFICANCE: Automatic cEEG analysis provides useful information in septic patients.",
keywords = "Automatic EEG, Delirium, EEG, Prognostication, Sepsis, cEEG",
author = "Olalla Urdanibia-Centelles and Nielsen, {Rikke M.} and Egill Rostrup and Esben Vedel-Larsen and Kirsten Thomsen and Miki Nikolic and Birger Johnsen and Kirsten M{\o}ller and Martin Lauritzen and Krisztina Benedek",
year = "2021",
month = sep,
doi = "10.1016/j.clinph.2021.05.013",
language = "English",
volume = "132",
pages = "2075--2082",
journal = "Clinical Neurophysiology",
issn = "1388-2457",
publisher = "Elsevier Ireland Ltd",
number = "9",

}

RIS

TY - JOUR

T1 - Automatic continuous EEG signal analysis for diagnosis of delirium in patients with sepsis

AU - Urdanibia-Centelles, Olalla

AU - Nielsen, Rikke M.

AU - Rostrup, Egill

AU - Vedel-Larsen, Esben

AU - Thomsen, Kirsten

AU - Nikolic, Miki

AU - Johnsen, Birger

AU - Møller, Kirsten

AU - Lauritzen, Martin

AU - Benedek, Krisztina

PY - 2021/9

Y1 - 2021/9

N2 - OBJECTIVE: In critical care, continuous EEG (cEEG) monitoring is useful for delirium diagnosis. Although visual cEEG analysis is most commonly used, automatic cEEG analysis has shown promising results in small samples. Here we aimed to compare visual versus automatic cEEG analysis for delirium diagnosis in septic patients.METHODS: We obtained cEEG recordings from 102 septic patients who were scored for delirium six times daily. A total of 1252 cEEG blocks were visually analyzed, of which 805 blocks were also automatically analyzed.RESULTS: Automatic cEEG analyses revealed that delirium was associated with 1) high mean global field power (p < 0.005), mainly driven by delta activity; 2) low average coherence across all electrode pairs and all frequencies (p < 0.01); 3) lack of intrahemispheric (fronto-temporal and temporo-occipital regions) and interhemispheric coherence (p < 0.05); and 4) lack of cEEG reactivity (p < 0.005). Classification accuracy was assessed by receiver operating characteristic (ROC) curve analysis, revealing a slightly higher area under the curve for visual analysis (0.88) than automatic analysis (0.74) (p < 0.05).CONCLUSIONS: Automatic cEEG analysis is a useful supplement to visual analysis, and provides additional cEEG diagnostic classifiers.SIGNIFICANCE: Automatic cEEG analysis provides useful information in septic patients.

AB - OBJECTIVE: In critical care, continuous EEG (cEEG) monitoring is useful for delirium diagnosis. Although visual cEEG analysis is most commonly used, automatic cEEG analysis has shown promising results in small samples. Here we aimed to compare visual versus automatic cEEG analysis for delirium diagnosis in septic patients.METHODS: We obtained cEEG recordings from 102 septic patients who were scored for delirium six times daily. A total of 1252 cEEG blocks were visually analyzed, of which 805 blocks were also automatically analyzed.RESULTS: Automatic cEEG analyses revealed that delirium was associated with 1) high mean global field power (p < 0.005), mainly driven by delta activity; 2) low average coherence across all electrode pairs and all frequencies (p < 0.01); 3) lack of intrahemispheric (fronto-temporal and temporo-occipital regions) and interhemispheric coherence (p < 0.05); and 4) lack of cEEG reactivity (p < 0.005). Classification accuracy was assessed by receiver operating characteristic (ROC) curve analysis, revealing a slightly higher area under the curve for visual analysis (0.88) than automatic analysis (0.74) (p < 0.05).CONCLUSIONS: Automatic cEEG analysis is a useful supplement to visual analysis, and provides additional cEEG diagnostic classifiers.SIGNIFICANCE: Automatic cEEG analysis provides useful information in septic patients.

KW - Automatic EEG

KW - Delirium

KW - EEG

KW - Prognostication

KW - Sepsis

KW - cEEG

UR - https://doi.org/10.1016/j.clinph.2021.05.013

UR - http://www.scopus.com/inward/record.url?scp=85110305439&partnerID=8YFLogxK

U2 - 10.1016/j.clinph.2021.05.013

DO - 10.1016/j.clinph.2021.05.013

M3 - Journal article

C2 - 34284242

VL - 132

SP - 2075

EP - 2082

JO - Clinical Neurophysiology

JF - Clinical Neurophysiology

SN - 1388-2457

IS - 9

ER -

ID: 66411548