Risk factors that predict delayed seizure detection on continuous electroencephalogram (cEEG) in a large sample size of critically ill patients

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Abstract

Objective: Majority of seizures are detected within 24 hours on continuous EEG (cEEG). Some patients have delayed seizure detection after 24 hours. The purpose of this research was to identify risk factors that predict delayed seizure detection and to determine optimal cEEG duration for various patient subpopulations. Methods: We retrospectively identified all patients ≥18 years of age who underwent cEEG at Cleveland clinic during calendar year 2016. Clinical and EEG data for all patients and time to seizure detection for seizure patients were collected. Results: Twenty-four hundred and two patients met inclusion criteria. Of these, 316 (13.2%) had subclinical seizures. Sixty-five (20.6%) patients had delayed seizures detection after 24 hours. Seizure detection increased linearly till 36 hours of monitoring, and odds of seizure detection increased by 46% for every additional day of monitoring. Delayed seizure risk factors included stupor (13.2% after 48 hours, P =.031), lethargy (25.9%, P =.013), lateralized (LPDs) (27.7%, P =.029) or generalized periodic discharges (GPDs) (33.3%, P =.022), acute brain insults (25.5%, P =.036), brain bleeds (32.8%, P =.014), especially multiple concomitant bleeds (61.1%, P <24 hours of monitoring appears sufficient. Previous studies have shown that coma and LPDs predict delayed seizure detection. We found that stupor and lethargy were also associated with delayed seizure detection. LPDs and GPDs were associated with delayed seizures. Other delayed seizure risk factors included acute brain insults, brain bleeds especially multiple concomitant bleeds, altered mental status as primary cEEG indication, and use of ASMs at cEEG initiation. Longer cEEG (≥48 hours) is suggested for these high-risk patients.

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Zawar, I., Briskin, I., & Hantus, S. (2022). Risk factors that predict delayed seizure detection on continuous electroencephalogram (cEEG) in a large sample size of critically ill patients. Epilepsia Open, 7(1), 131–143. https://doi.org/10.1002/epi4.12572

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