Brad K Kamitaki1, Alma Yum2, James Lee3, Shelly Rishty3, Kartik Sivaraaman4, Abdolreza Esfahanizadeh5, Ram Mani3, Stephen Wong3. 1. Department of Neurology, Rutgers-Robert Wood Johnson Medical School, 125 Paterson Street, Suite 6100 New Brunswick, NJ, 08901, United States. Electronic address: brad.kamitaki@rutgers.edu. 2. Division of Neurology, Denver Health Medical Center, University of Colorado School of Medicine, 681 Broadway Street, Denver, CO, 80203, United States. 3. Department of Neurology, Rutgers-Robert Wood Johnson Medical School, 125 Paterson Street, Suite 6100 New Brunswick, NJ, 08901, United States. 4. Abington Neurological Associates, 2325 Maryland Road, Suite 120, Willow Grove, PA, 19090, United States. 5. Department of Pediatrics, Rutgers-Robert Wood Johnson Medical School, 89 French Street, 2ndFloor, New Brunswick, NJ, 08901, United States.
Abstract
PURPOSE: To investigate the performance of seizure detection methods and nursing staff response in our epilepsy monitoring unit (EMU). METHODS: We retrospectively reviewed 38 EMU patient admissions over a 1-year period capturing 133 epileptic and non-epileptic seizures with associated video-EEG data. We recorded detailed seizure event characteristics for further analysis. RESULTS: Rates of seizure detection, alarm usage, and time to nursing response varied by seizure type. Patients self-activated the push button (PB) alarm for 31.1% of all seizures, but only 8.9% of focal impaired awareness (FIAS) and focal to bilateral tonic-clonic seizures (FBTCS). In comparison, the Persyst automated seizure alarm reliably detected both electrographic seizures (76.2% of electrographic seizures) and FIAS/FBTCS (87.2% of FIAS/FBTCS), with a false positive alarm rate (FAR) of 0.14/hour, or every 7.3 h. 11.4% of all seizures went unrecognized by nursing staff, of which the majority (80.0%) were FIAS. The PB alarm was of higher yield for alerting nurses to focal aware seizures (FAS) and psychogenic non-epileptic seizures (PNES) versus FIAS and FBTCS (p < 0.001). In contrast, nurses relied more on the automated Persyst software alarm to detect FIAS (p < 0.001). Time to nursing response was no different following audible alarm onset for the PB compared to the Persyst alarms (p = 0.14). CONCLUSION: Automated seizure detection software plays an important role in our EMU in seizure recognition, particularly for alerting nurses to FIAS. More rigorous studies are needed to determine the best utilization of various monitoring techniques and to promote high quality standards and patient safety in the EMU.
PURPOSE: To investigate the performance of seizure detection methods and nursing staff response in our epilepsy monitoring unit (EMU). METHODS: We retrospectively reviewed 38 EMU patient admissions over a 1-year period capturing 133 epileptic and non-epilepticseizures with associated video-EEG data. We recorded detailed seizure event characteristics for further analysis. RESULTS: Rates of seizure detection, alarm usage, and time to nursing response varied by seizure type. Patients self-activated the push button (PB) alarm for 31.1% of all seizures, but only 8.9% of focal impaired awareness (FIAS) and focal to bilateral tonic-clonic seizures (FBTCS). In comparison, the Persyst automated seizure alarm reliably detected both electrographic seizures (76.2% of electrographic seizures) and FIAS/FBTCS (87.2% of FIAS/FBTCS), with a false positive alarm rate (FAR) of 0.14/hour, or every 7.3 h. 11.4% of all seizures went unrecognized by nursing staff, of which the majority (80.0%) were FIAS. The PB alarm was of higher yield for alerting nurses to focal aware seizures (FAS) and psychogenic non-epilepticseizures (PNES) versus FIAS and FBTCS (p < 0.001). In contrast, nurses relied more on the automated Persyst software alarm to detect FIAS (p < 0.001). Time to nursing response was no different following audible alarm onset for the PB compared to the Persyst alarms (p = 0.14). CONCLUSION: Automated seizure detection software plays an important role in our EMU in seizure recognition, particularly for alerting nurses to FIAS. More rigorous studies are needed to determine the best utilization of various monitoring techniques and to promote high quality standards and patient safety in the EMU.
Authors: Taneeta Mindy Ganguly; Colin A Ellis; Danni Tu; Russell T Shinohara; Kathryn A Davis; Brian Litt; Jay Pathmanathan Journal: Neurology Date: 2022-04-11 Impact factor: 11.800
Authors: Mark L Scheuer; Scott B Wilson; Arun Antony; Gena Ghearing; Alexandra Urban; Anto I Bagić Journal: J Clin Neurophysiol Date: 2021-09-01 Impact factor: 2.590