Quantitative electroencephalography characteristics in delirium with various etiologies: A multicenter study
Julia van der A1, Robert Fleischmann2, Annerose Mengel3
1Department of Intensive Care Medicine, University Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands; Department of Psychiatry, University Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.
Neuroimage. Clinical
|August 19, 2025
Summary
Quantitative electroencephalography (qEEG) shows common neurophysiological patterns in delirium, regardless of its cause. Specific qEEG measures like peak frequency and delta/beta power consistently differed between delirious and non-delirious patients across subtypes.
Area of Science:
- Neuroscience
- Neurology
- Medical Imaging
Background:
- Delirium is an acute encephalopathy with diverse causes.
- Understanding the neurophysiological underpinnings of delirium is crucial for diagnosis and treatment.
- Quantitative electroencephalography (qEEG) offers objective measures of brain activity.
Purpose of the Study:
- To investigate if quantitative electroencephalography (qEEG) characteristics of delirium vary by etiological subtype or exhibit common neurophysiological patterns.
- To compare qEEG measures between delirious and non-delirious patients across different delirium etiologies.
Main Methods:
- A multicenter observational study analyzed qEEG data from 377 patients (173 delirious, 204 non-delirious).
- Delirium subtypes included post-stroke, medical, and postoperative, diagnosed per DSM-IV/5 criteria.
- Key qEEG measures analyzed were peak frequency, relative power (delta, beta), and phase lag index (PLI).
Main Results:
- Consistent spectral qEEG patterns were observed across all delirium subtypes compared to non-delirious controls.
- A decrease in peak frequency (SMD = -0.81) and relative beta power (SMD = -1.72) was noted.
- An increase in relative delta power (SMD = 1.44) was consistently found in delirious patients.
- Differences in phase lag index (PLI) between groups were small and inconsistent across subtypes.
Conclusions:
- Spectral qEEG characteristics reveal a common neurophysiological pathway of global EEG slowing in delirium, irrespective of etiology.
- Phase lag index (PLI) differences did not show consistent patterns across delirium subtypes.
- Future multicenter studies should harmonize data collection to differentiate shared and distinct neurophysiological changes in delirium.
