Delirium can be categorized into distinct clinical phenotypes based on the likely precipitating etiologies (causes). We previously identified an electroencephalography (EEG)-based signature of delirium, using spectral and complexity metrics of raw EEG recordings. In this retrospective observational study, we hypothesize that clinical delirium phenotypes are associated with characteristic spectral, complexity and functional connectivity patterns on scalp EEG. If the typical signatures associated with specific causes of delirium can be identified, we may be able to use the EEG signatures to guide delirium management in the future.
