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

脑电图 定量脑电图 医学 格拉斯哥昏迷指数 逻辑回归 癫痫 创伤性脑损伤 接收机工作特性 回顾性队列研究 曲线下面积 内科学 队列 麻醉 精神科
作者
Yilun Chen,Songlu Li,Wendong Ge,Jing Jin,Hsin Yi Chen,Daniel Doherty,Alison L Herman,Safa Kaleem,Kan Ding,Gamaleldin Osman,Christa B. Swisher,C.W. Smith,Carolina B. Maciel,Ayham Alkhachroum,Jong Woo Lee,Monica B. Dhakar,Emily J. Gilmore,Adithya Sivaraju,Lawrence J. Hirsch,Sacit Bulent Omay,Hal Blumenfeld,Kevin N Sheth,Aaron F. Struck,Brian L. Edlow,M. Brandon Westover,Jennifer A Kim
出处
期刊:Journal of Neurology, Neurosurgery, and Psychiatry [BMJ]
卷期号:94 (3): 245-249 被引量:1
标识
DOI:10.1136/jnnp-2022-329542
摘要

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).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.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)).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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