Literature DB >> 25099019

Monitoring epilepsy in the intensive care unit: current state of facts and potential interest of high density EEG.

Melanie Boly1, Rama Maganti.   

Abstract

PRIMARY
OBJECTIVE: To assess the current state of the art of epilepsy monitoring in intensive care unit (ICU). RESEARCH
DESIGN: Review article. METHODS AND PROCEDURES: A review of current scientific literature, as well as an illustrative case report. MAIN OUTCOMES AND
RESULTS: Recent continuous electroencephalography (cEEG) monitoring studies revealed that non-convulsive seizures are very common in ICU. Conventional EEG is insufficient to detect them. However, very long recordings, of more than 24 hours, are needed to reach a good sensitivity. Even if cEEG improves monitoring of epileptic patients in the intensive care unit (ICU), studies using intracranial recordings show that conventional montage cEEG is, however, insufficient to detect all neurological deterioration in patients in the ICU. This review discusses the potential interest of dense array scalp EEG recordings to increase the sensitivity of detection of epileptic events in non-responsive patients in the ICU and to possibly help improve their prognosis, by allowing an earlier start of their treatment.
CONCLUSIONS: Studies using dense array scalp EEG could potentially improve the detection and management of seizures in non-responsive patients in the ICU. Studies comparing this technique to conventional cEEG recordings are warranted.

Entities:  

Keywords:  Coma; neuroimaging; seizure

Mesh:

Substances:

Year:  2014        PMID: 25099019     DOI: 10.3109/02699052.2014.920525

Source DB:  PubMed          Journal:  Brain Inj        ISSN: 0269-9052            Impact factor:   2.311


  3 in total

1.  A predictive epilepsy index based on probabilistic classification of interictal spike waveforms.

Authors:  Jesse A Pfammatter; Rachel A Bergstrom; Eli P Wallace; Rama K Maganti; Mathew V Jones
Journal:  PLoS One       Date:  2018-11-06       Impact factor: 3.240

2.  An automated, machine learning-based detection algorithm for spike-wave discharges (SWDs) in a mouse model of absence epilepsy.

Authors:  Jesse A Pfammatter; Rama K Maganti; Mathew V Jones
Journal:  Epilepsia Open       Date:  2019-02-06

Review 3.  Prevention, Treatment, and Monitoring of Seizures in the Intensive Care Unit.

Authors:  Micheal Strein; John P Holton-Burke; LaTangela R Smith; Gretchen M Brophy
Journal:  J Clin Med       Date:  2019-08-07       Impact factor: 4.241

  3 in total

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