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Repository of Research and Investigative Information

Baqiyatallah University of Medical Sciences

Perioperative routine EEG can reliably predict de novo seizures after supratentorial craniotomy

(2021) Perioperative routine EEG can reliably predict de novo seizures after supratentorial craniotomy. Neurological Sciences. p. 6. ISSN 1590-1874

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Abstract

Background The contributing risk factors in development of seizure after supratentorial craniotomy, the optimal duration of prophylactic antiepileptic therapy, the high-risk patient to treat, and the drug of choice are subjects of debate as is the gold standard diagnostic tool for patient screening. Combining routine electroencephalography (EEG) with clinical data to identify high-risk patients and determine the ideal time of recording after surgery was the goal of this study. Methods In this prospective cohort, 59 patients were evaluated with three EEG recordings after different intervals of supratentorial craniotomy due to different etiologies and were followed for 9 months for development of seizures. Demographic and disease-related variables as well as EEG results were analyzed to determine the contributing risk factors for development of seizures. Results Neoplastic etiology and abnormal perioperative EEG (performed before surgery or in the first postoperative week) were the only independent variables associated with development of de novo seizure. Conclusion Routine EEG in the perioperative period and neoplastic etiology are two independent powerful predictors of developing seizure after supratentorial craniotomy and may help deciding whether to continue prophylactic antiepileptic medications for an extended period or not.

Item Type: Article
Keywords: EEG Craniotomy Seizure Antiepileptics postoperative seizures international-league classification craniectomy epilepsy ilae Neurosciences & Neurology
Page Range: p. 6
Journal or Publication Title: Neurological Sciences
Journal Index: ISI
Identification Number: https://doi.org/10.1007/s10072-021-05697-y
ISSN: 1590-1874
Depositing User: مهندس مهدی شریفی
URI: http://eprints.bmsu.ac.ir/id/eprint/9601

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