Characteristics and clinical value of early electroencephalography (EEG) after a first unprovoked seizure in children
Neurophysiologie Clinique, vol.53, no.1, 2023 (SCI-Expanded, Scopus)
- Publication Type: Article / Article
- Volume: 53 Issue: 1
- Publication Date: 2023
- Doi Number: 10.1016/j.neucli.2023.102848
- Journal Name: Neurophysiologie Clinique
- Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, BIOSIS, MEDLINE
- Keywords: EEG, First unprovoked seizure, Recurrence
- Ankara Yıldırım Beyazıt University Affiliated: Yes
Abstract
Objective: This study aimed to examine the timing and features of electroencephalography (EEG) as a predictor of seizure recurrence in children with a first unprovoked seizure. Methods: We retrospectively evaluated the medical records and EEG recordings of pediatric patients who presented within 24 h of a first unprovoked seizure between January 2018-December 2019 and had at least 1 year of pediatric neurology clinical follow-up. Results: The study included 108 patients (53.7% males) with a mean age of 98.75±57.75 months. Sixty-eight patients (63%) had an abnormal initial EEG, of which 55 (80.9%) were focal. The semiology of the first unprovoked seizure was focal in 50% of the patients and correlated with initial EEG findings (p<0.001). Forty-three patients had seizure recurrence during the follow-up period of mean 26.86±7.39 months. Recurrence was observed in the first 6 months in 30 patients and occurred twice in 4 patients. An abnormal EEG after the first unprovoked seizure was found to be an independent risk factor for recurrence, with a 2.42-fold higher recurrence risk in patients with focal EEG abnormalities compared to those with a normal EEG (p = 0.044). Analysis of 7 different timing patterns up to 96 h after the first unprovoked seizure showed that EEG timing was not associated with abnormality detection. Discussion: Our study showed that EEG abnormalities, especially focal abnormalities, after a first unprovoked seizure are a predictor of seizure recurrence. But the rate of detection of EEG abnormalities was not related to the timing of EEG recording, relative to seizure occurrence.