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Automatic continuous EEG signal analysis for diagnosis of delirium in patients with sepsis
Olalla Urdanibia-Centelles1, Rikke M Nielsen2, Egill Rostrup3
1Department of Clinical Neurophysiology, The Neuroscience Centre, Rigshospitalet, University of Copenhagen, Valdemar Hansens Vej 1-23, Glostrup, Denmark; Center for Healthy Aging and Department of Neuroscience, University of Copenhagen, Blegdamsvej 3B, 2200 Copenhagen, Denmark.
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.
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