ArticleNeurocritical care2024
Novel EEG Metric Correlates with Intracranial Pressure in an Animal Model.
Article in Neurocritical care, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed, 3 citations in OpenAlex.
- Characterization of intracranial pressure variations in ventricular and subarachnoid spaces of the rat brain.Journal of applied physiology (Bethesda, Md. : 1985) · 2026Article
- Association between EEG metrics and continuous cerebrovascular autoregulation assessment: a scoping review.British journal of anaesthesia · 2024Article
- Article
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Authors and funding
9 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIntracranial pressure (ICP) can be continuously and reliably measured using invasive monitoring through an external ventricular catheter or an intraparenchymal probe. We explore electroencephalography (EEG) to identify a reliable real-time noninvasive ICP correlate.
methodsUsing a previously described porcine model of intracranial hypertension, we examined the cross correlation between ICP time series and the slope of the EEG power spectral density as described by ϕ. We calculated ϕ as tan
resultsThe mean correlation between ϕ angle and ICP was - 0.85 (0.15); the mean correlation with cerebral perfusion pressure was 0.92 (0.02). Significant correlation occurred at zero lag. In the absence of intracranial hypertension, the absolute value of the ϕ angle was greater than 0.9 (mean 0.936 radians). However, during extreme intracranial hypertension causing cerebral circulatory arrest, the ϕ angle is on average below 0.9 radians (mean 0.855 radians).
conclusionsEEG ϕ angle is a promising real-time noninvasive measure of ICP/cerebral perfusion using surface electroencephalography.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.