Abstract
Background Delirium is a common disorder affecting around 31% of patients in the intensive care unit (ICU). Delirium assessment scores such as the Confusion Assessment Method (CAM) are time-consuming, they cannot differentiate between different types of delirium and their etiologies, and they may have low sensitivities in the clinical setting. While today, electroencephalography (EEG) is increasingly being applied to delirious patients in the ICU, a lack of clear cut EEG signs, leads to inconsistent assessments.
Methods We therefore conducted a scoping review on EEG findings in delirium. One thousand two hundred thirty-six articles identified through database search on PubMed and Embase were reviewed. Finally, 33 original articles were included in the synthesis.
Results EEG seems to offer manifold possibilities in diagnosing delirium. All 33 studies showed a certain degree of qualitative or quantitative EEG alterations in delirium. Thus, normal routine (rEEG) and continuous EEG (cEEG) make presence of delirium very unlikely. All 33 studies used different research protocols to at least some extent. These include differences in time points, duration, conditions, and recording methods of EEG, as well as different patient populations, and diagnostic methods for delirium. Thus, a quantitative synthesis and common recommendations are so far elusive.
Conclusion Future studies should compare the different methods of EEG recording and evaluation to identify robust parameters for everyday use. Evidence for quantitative bi-electrode delirium detection based on increased relative delta power and decreased beta power is growing and should be further pursued. Additionally, EEG studies on the evolution of a delirium including patient outcomes are needed.
Item Type: | Journal article |
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Faculties: | Medicine > Institute for Stroke and Dementia Research (ISD) |
Subjects: | 600 Technology > 610 Medicine and health |
URN: | urn:nbn:de:bvb:19-epub-104693-6 |
ISSN: | 1471-2377 |
Language: | English |
Item ID: | 104693 |
Date Deposited: | 13. Jul 2023, 13:44 |
Last Modified: | 04. Jan 2024, 12:07 |
DFG: | Gefördert durch die Deutsche Forschungsgemeinschaft (DFG) - 491502892 |