Quantitative epileptiform burden and electroencephalography background features predict post-traumatic epilepsy

  • Yilun Chen
  • , Songlu Li
  • , Wendong Ge
  • , Jin Jing
  • , Hsin Yi Chen
  • , Daniel Doherty
  • , Alison Herman
  • , Safa Kaleem
  • , Kan Ding
  • , Gamaleldin Osman
  • , Christa B. Swisher
  • , Christine Smith
  • , Carolina B. Maciel
  • , Ayham Alkhachroum
  • , Jong Woo Lee
  • , Monica B. Dhakar
  • , Emily J. Gilmore
  • , Adithya Sivaraju
  • , Lawrence J. Hirsch
  • , Sacit B. Omay
  • Hal Blumenfeld, Kevin N. Sheth, Aaron F. Struck, Brian L. Edlow, M. Brandon Westover, Jennifer A. Kim

Research output: Contribution to journalArticlepeer-review

16 Scopus citations

Abstract

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 (PTE 1). Methods We performed a multicentre, retrospective case-control study of patients with TBI. 63 PTE 1 patients were matched with 63 non-PTE 1 patients by admission Glasgow Coma Scale score, age and sex. We evaluated the association of quantitative electroencephalography features with PTE 1 using 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 PTE 1 risk 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 PTE 1 prediction. Future trials should incorporate quantitative electroencephalography features to validate this enhancement of PTE risk stratification models.

Original languageEnglish
Pages (from-to)245-249
Number of pages5
JournalJournal of Neurology, Neurosurgery and Psychiatry
Volume94
Issue number3
DOIs
StatePublished - Mar 2023

Keywords

  • EEG
  • EPILEPSY
  • TRAUMATIC BRAIN INJURY

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