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Quantitative EEG During Critical Illness Correlates with Patterns of Long-Term Cognitive Impairment.
- Source :
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Clinical EEG and neuroscience [Clin EEG Neurosci] 2022 Sep; Vol. 53 (5), pp. 435-442. Date of Electronic Publication: 2020 Dec 08. - Publication Year :
- 2022
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Abstract
- Objective: Many intensive care unit (ICU) survivors suffer disabling long-term cognitive impairment (LTCI) after critical illness. We compared EEG characteristics during critical illness with patients' 1-year neuropsychological outcomes.<br />Methods: We performed a post hoc analysis of patients in the BRAIN-ICU study who had undergone EEG for clinical purposes during admission (n = 10). All survivors underwent formal cognitive assessments at 12-month follow-up. We evaluated EEGs by conventional visual inspection and computed 10 quantitative features. We explored associations between EEG and patterns of LTCI using Wilcoxon rank-sum tests and Spearman's rank correlations.<br />Results: Of 521 Vanderbilt patients enrolled in the parent study, 24 had EEG recordings during admission. Ten survivors had EEG tracings available and completed follow-up cognitive testing. All but one inpatient EEG showed generalized background slowing. All patients demonstrated cognitive impairment in at least one domain at follow-up. The most common deficits occurred in delayed memory (DM-median index 62) and visuospatial/constructional (VC-median index 69) domains. Relative alpha power correlated with VC score (ρ = 0.78, P = .008). Peak interhemispheric coherence correlated negatively with DM (ρ = -0.81, P = .018).<br />Conclusions: Quantitative EEG features during critical illness correlated with domain-specific cognitive performance in our small cohort of ICU survivors. Further study in larger prospective cohorts is required to determine whether these relationships hold.<br />Significance: EEG may serve as a prognostic biomarker predicting patterns of long-term cognitive impairment.
Details
- Language :
- English
- ISSN :
- 2169-5202
- Volume :
- 53
- Issue :
- 5
- Database :
- MEDLINE
- Journal :
- Clinical EEG and neuroscience
- Publication Type :
- Academic Journal
- Accession number :
- 33289394
- Full Text :
- https://doi.org/10.1177/1550059420978009