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. OmayHal Blumenfeld, Kevin N. Sheth, Aaron F. Struck, Brian L. Edlow, M. Brandon Westover, Jennifer A. Kim

Research output: Contribution to journalArticlepeer-review


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 (US)
Pages (from-to)245-249
Number of pages5
JournalJournal of Neurology, Neurosurgery and psychiatry
Issue number3
StatePublished - Mar 2023


  • EEG

ASJC Scopus subject areas

  • Surgery
  • Clinical Neurology
  • Psychiatry and Mental health


Dive into the research topics of 'Quantitative epileptiform burden and electroencephalography background features predict post-traumatic epilepsy'. Together they form a unique fingerprint.

Cite this