A Trial of Real-Time Electrographic Seizure Detection by Neuro-ICU Nurses Using a Panel of Quantitative EEG Trends
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ORIGINAL WORK
A Trial of Real‑Time Electrographic Seizure Detection by Neuro‑ICU Nurses Using a Panel of Quantitative EEG Trends Jennifer H. Kang1* , G. Clay Sherill1, Saurabh R. Sinha1,2 and Christa B. Swisher1 © 2019 This is a U.S. government work and its text is not subject to copyright protection in the United States; however, its text may be subject to foreign copyright protection
Abstract Background: Non-convulsive seizures (NCS) are a common occurrence in the neurologic intensive care unit (NeuroICU) 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 boardcertified 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. Keywords: Quantitative EEG, qEEG, Seizures, ICU, EEG, Non-convulsive seizures Introduction Non-convulsive seizures (NCS) and non-convulsive status epilepticus (NCSE) occur in 8–48% of patients admitted to the intensive care unit (ICU) [1–4] and are associated with worse outcomes [5]. Early identification of NCS and NCSE *Correspondence: [email protected] 1 Department of Neurology, Duke University Medical Center, DUMC 2905, Durham, NC 27710, USA Full list of author information is available at the end of the article
enables timely intervention with improved likelihood of seizure control [6–8]. A cross-sect
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