Automatic continuous EEG signal analysis for diagnosis of delirium in patients with sepsis
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Automatic continuous EEG signal analysis for diagnosis of delirium in patients with sepsis. / Urdanibia-Centelles, Olalla; Nielsen, Rikke M.; Rostrup, Egill; Vedel-Larsen, Esben; Thomsen, Kirsten; Nikolic, Miki; Johnsen, Birger; Møller, Kirsten; Lauritzen, Martin; Benedek, Krisztina.
In: Clinical Neurophysiology, Vol. 132, No. 9, 2021, p. 2075-2082.Research output: Contribution to journal › Journal article › Research › peer-review
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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
Y1 - 2021
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.
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.
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: 274224218