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Quantitative epileptiform burden and electroencephalography background features predict post-traumatic epilepsy.
Chen, Yilun; Li, Songlu; Ge, Wendong; Jing, Jin; Chen, Hsin Yi; Doherty, Daniel; Herman, Alison; Kaleem, Safa; Ding, Kan; Osman, Gamaleldin; Swisher, Christa B; Smith, Christine; Maciel, Carolina B; Alkhachroum, Ayham; Lee, Jong Woo; Dhakar, Monica B; Gilmore, Emily J; Sivaraju, Adithya; Hirsch, Lawrence J; Omay, Sacit B; Blumenfeld, Hal; Sheth, Kevin N; Struck, Aaron F; Edlow, Brian L; Westover, M Brandon; Kim, Jennifer A.
Afiliação
  • Chen Y; Neurology, Yale School of Medicine, New Haven, Connecticut, USA.
  • Li S; Neurology, Yale School of Medicine, New Haven, Connecticut, USA.
  • Ge W; Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA.
  • Jing J; Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA.
  • Chen HY; Neurology, Yale School of Medicine, New Haven, Connecticut, USA.
  • Doherty D; Neurology, Yale School of Medicine, New Haven, Connecticut, USA.
  • Herman A; Neurology, Yale School of Medicine, New Haven, Connecticut, USA.
  • Kaleem S; Neurology, Duke University School of Medicine, Durham, North Carolina, USA.
  • Ding K; Neurology, UT Southwestern Medical Center, Dallas, Texas, USA.
  • Osman G; Neurology, Henry Ford Health System, Detroit, Michigan, USA.
  • Swisher CB; Neurology, Duke University School of Medicine, Durham, North Carolina, USA.
  • Smith C; Neurology, University of Florida College of Medicine, Gainesville, Florida, USA.
  • Maciel CB; Neurology, Yale School of Medicine, New Haven, Connecticut, USA.
  • Alkhachroum A; Neurology, University of Florida College of Medicine, Gainesville, Florida, USA.
  • Lee JW; Neurology, University of Miami Miller School of Medicine, Miami, Florida, USA.
  • Dhakar MB; Neurology, Jackson Memorial Hospital, Miami, Florida, USA.
  • Gilmore EJ; Neurology, Brigham and Women's Hospital, Boston, Massachusetts, USA.
  • Sivaraju A; Neurology, Emory University School of Medicine, Atlanta, Georgia, USA.
  • Hirsch LJ; Neurology, Yale School of Medicine, New Haven, Connecticut, USA.
  • Omay SB; Neurology, Yale School of Medicine, New Haven, Connecticut, USA.
  • Blumenfeld H; Neurology, Yale School of Medicine, New Haven, Connecticut, USA.
  • Sheth KN; Neurosurgery, Yale School of Medicine, New Haven, Connecticut, USA.
  • Struck AF; Neurology, Yale School of Medicine, New Haven, Connecticut, USA.
  • Edlow BL; Neurology, Yale School of Medicine, New Haven, Connecticut, USA.
  • Westover MB; Neurology, University of Wisconsin-Madison School of Medicine and Public Health, Madison, Wisconsin, USA.
  • Kim JA; Neurology, William S Middleton Memorial Veterans Hospital, Madison, Wisconsin, USA.
J Neurol Neurosurg Psychiatry ; 94(3): 245-249, 2023 03.
Article em En | MEDLINE | ID: mdl-36241423
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 (PTE1).

METHODS:

We performed a multicentre, retrospective case-control study of patients with TBI. 63 PTE1 patients were matched with 63 non-PTE1 patients by admission Glasgow Coma Scale score, age and sex. We evaluated the association of quantitative electroencephalography features with PTE1 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 PTE1 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 PTE1 prediction. Future trials should incorporate quantitative electroencephalography features to validate this enhancement of PTE risk stratification models.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Epilepsia Pós-Traumática / Lesões Encefálicas Traumáticas Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: J Neurol Neurosurg Psychiatry Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Epilepsia Pós-Traumática / Lesões Encefálicas Traumáticas Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: J Neurol Neurosurg Psychiatry Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos