• Hideaki Tanaka, Jean Gotman, Hui Ming Khoo, André Olivier, Jeffery Hall, and François Dubeau.
• 1Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada.
• J. Neurosurg. 2020 Dec 1; 133 (6): 186318721863-1872.

ObjectiveThe authors sought to determine which neurophysiological seizure-onset features seen during scalp electroencephalography (EEG) and intracerebral EEG (iEEG) monitoring are predictors of postoperative outcome in a large series of patients with drug-resistant focal epilepsy who underwent resective surgery.MethodsThe authors retrospectively analyzed the records of 75 consecutive patients with focal epilepsy, who first underwent scalp EEG and then iEEG (stereo-EEG) for presurgical assessment and who went on to undergo resective surgery between 2004 and 2015. To determine the independent prognostic factors from the neurophysiological scalp EEG and iEEG seizure-onset information, univariate and standard multivariable logistic regression analyses were used. Since scalp EEG and iEEG data were recorded at different times, the authors matched scalp seizures with intracerebral seizures for each patient using strict criteria.ResultsA total of 3057 seizures were assessed. Forty-eight percent (36/75) of patients had a favorable outcome (Engel class I-II) after a minimum follow-up of at least 1 year. According to univariate analysis, a localized scalp EEG seizure onset (p < 0.001), a multilobar intracerebral seizure-onset zone (SOZ) (p < 0.001), and an extended SOZ (p = 0.001) were significantly associated with surgical outcome. According to multivariable analysis, the following two independent factors were found: 1) the ability of scalp EEG to localize the seizure onset was a predictor of a favorable postoperative outcome (OR 6.073, 95% CI 2.011-18.339, p = 0.001), and 2) a multilobar SOZ was a predictor of an unfavorable outcome (OR 0.076, 95% CI 0.009-0.663, p = 0.020).ConclusionsThe study findings show that localization at scalp seizure onset and a multilobar SOZ were strong predictors of surgical outcome. These predictors can help to select the better candidates for resective surgery.

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