337 Quantitative Analysis of Admission Electroencephalography Predicts Post-Traumatic Epilepsy After Severe Traumatic Brain Injury

Abstract

INTRODUCTION: Up to one-third of severe traumatic brain injury (TBI) patients develop post-traumatic epilepsy (PTE), often years after their injury. Currently, there is no validated predictive model to identify patients at high risk for PTE. METHODS: We retrospectively analyzed a prospective database of severe TBI patients treated at a single level one trauma center from 2012 through 2018. Outcomes were recorded with the Expanded Glasgow Outcomes Scale (GOSE) at 6- and 12-months post-injury. We identified a cohort of patients who survived to two years and did not have an early post-traumatic seizure, defined as a seizure within 7 days of initial injury. From this cohort, we matched patients with PTE to those without using age and Glasgow coma scale score at admission. All patients underwent continuous EEG for 3-5 days upon admission, and a board-certified epileptologist identified 5-minute artifact-free segment for analysis. We extracted qEEG features, described them with qualitative statistics, and developed a logistic regression model using backwards selection. RESULTS: We identified 27 patients with PTE and 23 without who survived two years post-injury. The median time to onset of PTE was 7.2 months post-trauma and GOSE was similar when stratified by PTE at 6- and 12-months (p > 0.73). On qEEG analysis, patients with PTE had higher spectral power in the delta frequencies (p = 0.003), more variance in the delta and theta frequencies (p < 0.04), a higher mean amplitude (p = 0.01), and peak envelope (p = 0.01). On multivariate modeling, delta power (Odds Ratio [OR] 1.8), theta power (OR 0.2), and rhythmic spectrum (1.7) all increased risk of PTE and had an AUC of 0.85 for predicting PTE. CONCLUSIONS: In a cohort of severe TBI patients, quantitative qEEG features in the acute phase after injury identified future risk of PTE.