A Trial of Real-Time Electrographic Seizure Detection by Neuro-ICU Nurses Using a Panel of Quantitative EEG Trends View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-02-20

AUTHORS

Jennifer H. Kang, G. Clay Sherill, Saurabh R. Sinha, Christa B. Swisher

ABSTRACT

BACKGROUND: Non-convulsive seizures (NCS) are a common occurrence in the neurologic intensive care unit (Neuro-ICU) and are associated with worse outcomes. Continuous electroencephalogram (cEEG) monitoring is necessary for the detection of NCS; however, delays in interpretation are a barrier to early treatment. Quantitative EEG (qEEG) calculates a time-compressed simplified visual display from raw EEG data. This study aims to evaluate the performance of Neuro-ICU nurses utilizing bedside, real-time qEEG interpretation for detecting recurrent NCS. METHODS: This is a prospective, single-institution study of patients admitted to the Duke Neuro-ICU between 2016 and 2018 who had NCS identified on traditional cEEG review. The accuracy of recurrent seizure detection on hourly qEEG review by bedside Neuro-ICU nurses was compared to the gold standard of cEEG interpretation by two board-certified neurophysiologists. The nurses first received brief qEEG training, individualized for their specific patient. The bedside qEEG display consisted of rhythmicity spectrogram (left and right hemispheres) and amplitude-integrated EEG (left and right hemispheres) in 1-h epochs. RESULTS: Twenty patients were included and 174 1-h qEEG blocks were analyzed. Forty-seven blocks contained seizures (27%). The sensitivity was 85.1% (95% CI 71.1-93.1%), and the specificity was 89.8% (82.8-94.2%) for the detection of seizures for each 1-h block when compared to interpretation of conventional cEEG by two neurophysiologists. The false positive rate was 0.1/h. Hemispheric seizures (> 4 unilateral EEG electrodes) were more likely to be correctly identified by nurses on qEEG than focal seizures (≤ 4 unilateral electrodes) (p = 0.03). CONCLUSIONS: After tailored training sessions, Neuro-ICU nurses demonstrated a good sensitivity for the interpretation of bedside real-time qEEG for the detection of recurrent NCS with a low false positive rate. qEEG is a promising tool that may be used by non-neurophysiologists and may lead to earlier detection of NCS. More... »

PAGES

1-9

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s12028-019-00673-z

DOI

http://dx.doi.org/10.1007/s12028-019-00673-z

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1112260197

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30788707


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Download the RDF metadata as:  json-ld nt turtle xml License info

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RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s12028-019-00673-z'


 

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