Electrographic Seizure Detection by Neuroscience Intensive Care Unit Nurses via Bedside Real-Time Quantitative EEG

Abstract

Objective:Our primary objective was to determine the performance of real-time Neuroscience ICU (Neuro ICU) nurse interpretation of quantitative EEG (qEEG) at the bedside for seizure detection. Secondary objectives included determining nurse time to seizure detection and assessing factors that influenced nurse accuracy.Methods:Nurses caring for Neuro ICU patients undergoing cEEG were trained using a 1-hour qEEG panel (rhythmicity spectrogram and amplitude-integrated EEG) bedside display. Nurses’ hourly interpretations were compared to post-hoc cEEG review by two neurophysiologists as the gold standard. Diagnostic performance, time to seizure detection as compared to standard of care (SOC), and effects of other factors on nurse accuracy were calculated.Results:109 patients and 65 nurses were studied. Eight patients had seizures during the study period (7%). Nurse sensitivity and specificity for the detection of seizures were 74% and 92%, respectively. Mean nurse time to seizure detection was significantly shorter than SOC by 132 minutes (Cox proportional hazard ratio 6.96). Inaccurate nurse interpretation was associated with increased hours monitored and presence of brief rhythmic discharges.Conclusions:This prospective study of real-time nurse interpretation of qEEG for seizure detection in Neuro ICU patients showed clinically adequate sensitivity and specificity. Time to seizure detection was less than that of SOC.Classification of Evidence:This study provides Class I evidence that Neuro ICU nurse interpretation of qEEG detects seizures in adults with a sensitivity of 74% and specificity of 92% as compared to traditional cEEG review.Clinical Trial Registration Number: NCT02082873

Challenges and Prospects in Epilepsy Monitoring Units: A Comprehensive Review of Logistic Barriers

“…Besides, several studies have suggested that non-EEG experts such as bedside ICU personnel can be trained in the acquisition and troubleshooting of EEGs, as well as screening uninterrupted raw EEG for seizure detection purposes [ 22 , 23 ].…”

Utility and rationale for continuous EEG monitoring: a primer for the general intensivist

“…Trends may include spectral power (amplitude of individual frequency bands summed over time), power ratios, variability, rhythmicity, asymmetry, and some tools for spike detection. With training, critical care nurses and other non-neurophysiologists can accurately assess panels displaying real-time qEEG measures such as spectral power, typically reviewing short segments of 15–60 min at a time to identify periods of high-suspicion EEG activity [ 36 , 202 , 203 ]. Following brief qEEG interpretation training 65 ICU nurses achieved 74% sensitivity and 92% specificity in identifying seizures, detecting these seizures 132 min faster than standard neurophysiology practices, although detecting brief events may necessitate zooming in on shorter EEG epochs [ 203 ].…”

“…With training, critical care nurses and other non-neurophysiologists can accurately assess panels displaying real-time qEEG measures such as spectral power, typically reviewing short segments of 15–60 min at a time to identify periods of high-suspicion EEG activity [ 36 , 202 , 203 ]. Following brief qEEG interpretation training 65 ICU nurses achieved 74% sensitivity and 92% specificity in identifying seizures, detecting these seizures 132 min faster than standard neurophysiology practices, although detecting brief events may necessitate zooming in on shorter EEG epochs [ 203 ]. Integrating qEEG interpretation training with user-friendly tools empowers non-experts, including critical care nurses, to monitor EEG data for potential seizure activity effectively, promising faster and more accurate seizure detection and improved intervention timing and quality.…”

“…This approach significantly accelerates the identification of potential electrographic seizures. In one study, ICU nurses employing qEEG detected seizures in 94% of patients with confirmed diagnoses on EEG recordings [ 204 ], leading to shorter seizure detection latency compared to conventional practice involving intermittent review by clinical neurophysiologists [ 203 ]. Emerging tools utilizing artificial intelligence-powered seizure detection are clinically available, empowering nurses to promptly identify seizures, with some methods even converting EEG data into audible frequency spectra to aid in early detection [ 205 , 206 ].…”

Nurses

“…In this issue of Neurology ® Clinical Practice , Kaleem et al 6 report on a prospective single-center study that evaluated the performance of neuro-ICU nurses for seizure detection by real-time bedside qEEG interpretation. In addition, the authors evaluated time to seizure detection and factors associated with interpretation inaccuracy.…”