Early Prediction of Epilepsy after Encephalitis in Childhood Based on EEG and Clinical Features

Autor: Xiaojuan Sun, Jinhua Zhao, Chunyun Guo, Xiaoxiao Zhu
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Emergency Medicine International, Vol 2023 (2023)
Druh dokumentu: article
ISSN: 2090-2859
DOI: 10.1155/2023/8862598
Popis: Objective. The present study was designed to establish and evaluate an early prediction model of epilepsy after encephalitis in childhood based on electroencephalogram (ECG) and clinical features. Methods. 255 patients with encephalitis were randomly divided into training and verification sets and were divided into postencephalitic epilepsy (PE) and no postencephalitic epilepsy (no-PE) according to whether epilepsy occurred one year after discharge. Univariate and multivariate logistic regression analyses were used to screen the risk factors for PE. The identified risk factors were used to establish and verify a model. Results. This study included 255 patients with encephalitis, including 209 in the non-PE group and 46 in the PE group. Univariate and multiple logistic regression analysis showed that hemoglobin (OR = 0.968, 95% CI = 0.951–0.958), epilepsy frequency (OR = 0.968, 95% CI = 0.951–0.958), and ECG slow wave/fast wave frequency (S/F) in the occipital region were independent influencing factors for PE (P
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