Abstracts

Rationale: A primary purpose of continuous EEG (cEEG) monitoring in hospitalized patient is to detect seizures. There is frequently a delay between ordering and placement of EEG due to the technical and logistical barriers associated with conventional cEEG. The advent of rapid-EEG technologies makes it possible to shorten this duration. Here we estimate how many patients had seizures missed due to delays in conventional EEG monitoring.

Methods: 250 consecutive adult patients who underwent conventional EEG monitoring at the University of Wisconsin Hospital and Clinics between 2019 and 2020 were retrospectively chart reviewed to determine the time at which cEEG was ordered, demographic and EEG information was extracted from the chart and EEG were reviewed as needed for missing information. Patients were stratified by use of anti-seizure medications (ASM) prior to cEEG and into LOW, MED, HIGH risk groups based on 2HELPS2B score (0, 1, or >1). 2HELPS2B was calculated from the first hour of EEG. The mean delay (presented with 95% range) to cEEG was recorded. Covariates analyzed for influence on delay to cEEG were location of EEG (ICU, emergency department, or general floor), if the EEG was performed after-hours and whether patients went on to have seizures or not. The effects of ASM on time to 1st seizure was performed using Cox survival analysis with log-rank test. If significant, the estimated time to 1st seizure would be adjusted in the following Monte Carlo simulation. To estimate the number of patients who had a seizure missed during the delay period, three Monte Carlo simulations (500 trials) were performed, one for each 2HELPS2B risk categories (LOW, MED, HIGH), using random sampling with replacement from the distribution of the time to 1^st seizure on cEEG and the distribution of the delay to cEEG.

Results: The mean delay from EEG order to performing EEG was 2.00H (0.25-5.00H) in the total cohort, 2.14H (0.25-4.40H) in patients who had a seizure, 1.94H (0.25-5.00H) in those who did not. The difference in delays was not significant p=0.43. In EEG ordered after-hours, the mean delay was 1.90H (0.25-4.65H) and during business hours, it was 2.14H (0.25-6.0H). The difference in delays was not significant p=0.16. The place of EEG: ICU, Floor, and ED did not have a significant difference in delay (p=0.83). FIGURE 1 is a box plot of some results. ASM did not affect time to 1^st seizure in the LOW (p=0.37), MED (p=0.44), or HIGH (p=0.12) risk groups and was therefore not used in adjustment. 

The estimated % of patients who had a missed seizure in the delay period for LOW risk group (2HELPS2B=0) was 0.8% (95% CI 0.0-3.2%), for the MED risk group (2HELPS2B=1) was 10.4% (95% CI 3.3-18.3%) and for the HIGH risk group (2HELPS2B >1), was 17.1% (95% CI 2.8-36.1%).

Conclusions: UW Hospital has 24-hour in-house EEG technologists and still has a mean delay of 2 Hours from order to start of cEEG. In high-risk patients, around 17.1% have a seizure missed during the delay. Prophylactic treatment with ASM did not affect time to 1st seizure. Timely EEG is necessary for efficient diagnosis and targeted treatment of hospitalized patients at risk for seizures.

Funding: Please list any funding that was received in support of this abstract.: None.