Background Post-traumatic epilepsy (PTE) is a severe complication of traumatic brain injury (TBI). Electroencephalography aids early post-traumatic seizure diagnosis, but its optimal utility for PTE prediction remains unknown. We aim to evaluate the contribution of quantitative electroencephalograms to predict first-year PTE (PTE1). Methods We performed a multicentre, retrospective case–control study of patients with TBI. 63 PTE1patients were matched with 63 non-PTE1patients by admission Glasgow Coma Scale score, age and sex. We evaluated the association of quantitative electroencephalography features with PTE1using logistic regressions and examined their predictive value relative to TBI mechanism and CT abnormalities. Results In the matched cohort (n=126), greater epileptiform burden, suppression burden and beta variability were associated with 4.6 times higher PTE1risk based on multivariable logistic regression analysis (area under the receiver operating characteristic curve, AUC (95% CI) 0.69 (0.60 to 0.78)). Among 116 (92%) patients with available CT reports, adding quantitative electroencephalography features to a combined mechanism and CT model improved performance (AUC (95% CI), 0.71 (0.61 to 0.80) vs 0.61 (0.51 to 0.72)). Conclusions Epileptiform and spectral characteristics enhance covariates identified on TBI admission and CT abnormalities in PTE1prediction. Future trials should incorporate quantitative electroencephalography features to validate this enhancement of PTE risk stratification models.
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Chen et al. (2022) studied this question.
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