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Citation
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Pease M, Elmer J, Shahabadi AZ, Mallela AN, Ruiz-Rodriguez JF, Sexton D, Barot N, González-Martínez JA, Shutter L, Okonkwo DO, Castellano JF. Epilepsia 2023; ePub(ePub): ePub. |
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Abstract
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OBJECTIVE: Post-traumatic epilepsy (PTE) develops in as many as one-third of severe traumatic brain injury (TBI) patients, often years after injury. Analysis of early electroencephalography (EEG) features, both standardized visual (viEEG) interpretation and quantitative EEG (qEEG) analysis, may aid early identification of patients at high risk for PTE.
METHODS: We performed a case-control study using a prospective database of severe TBI patients treated at a single center from 2011-2018. We identified patients who survived two years post-injury and matched patients with PTE to those without using age and admission Glasgow Coma Scale score. A neuropsychologist recorded outcomes at one-year using the Expanded Glasgow Outcomes Scale (GOSE). All patients underwent continuous EEG for 3-5 days. A board-certified epileptologist, blinded to outcomes, described viEEG features using standardized descriptions. We extracted fourteen qEEG features from an early 5-minute epoch, described them using qualitative statistics, then developed two multivariable models to predict long-term risk of PTE (random forest and logistic regression).
RESULTS: We identified 27 patients with and 35 without PTE. GOSE were similar at one-year (p=0.93). The median time to onset of PTE was 7.2 months post-trauma (Interquartile range: 2.2-22.2 months). None of the viEEG features were different between the groups. On qEEG, the PTE cohort had higher spectral power in the delta frequencies, more power variance in the delta and theta frequencies, and higher peak envelope (all p<0.01). Using random forest, combining qEEG and clinical features, had an area under the curve (AUC) of 0.76. Using logistic regression, increases in the delta/theta power ratio (odds ratio [OR]: 1.3; p<0.01) and peak envelope (OR 1.1; p<0.01) predicted risk for PTE. SIGNIFICANCE: In a cohort of severe TBI patients, acute phase EEG features may predict post-traumatic epilepsy. Predictive models, as applied to this study, may help identify patients at high risk for PTE, assist early clinical management, and guide patient selection for clinical trials.
Language: en |