Analysis on the Clinical Value of Electroencephalogram in Diagnosis of Epilepsy

  • Changmin Ke
  • Peiping Wang
  • Chuna Zheng
DOI: https://doi.org/10.18686/aem.v9i3.168
Keywords: Electroencephalogram, Epilepsy, Clinical Diagnosis, Clinical Value

Abstract

Objective: To study the clinical value of electroencephalogram (EEG) in the diagnosis of epilepsy. Methods: 80 patients with epilepsy in the Fifth Affiliated Hospital of Sun Yat-sen University from January to December 2019 were taken as research objects. EEG was applied to diagnose and analyze the electrical activity of these patients, results of which were compared with that of clinical diagnosis. Results: According to the statistics, the number of patients with epilepsy diagnosed by clinical manifestations and EEG was 78 and 75 respectively. The accuracy of EEG was calculated to be 96.2%. There was no significant difference between the diagnostic results of these two methods, and the results didn’t reach statistical significance (p>0.05). Conclusion: EEG has high accuracy in detecting and diagnosing epilepsy in clinic, which is worth promoting.

References

[1] Gu G. Analysis on the results of EEG for children with epilepsy at different ages (in Chinese). Journal of Modern Electrophysiology 2020; (2): 31-33.

[2] Fang R, Zhuang J, Yang Y, et al. Analysis of clinical characteristics and EEG for children with status epilepticus (in Chinese). Journal of Apoplexy and Nervous Diseases 2020; (3): 209-212.

[3] Zhang W. Diagnostic value of EEG for patients with epilepsy secondary to cerebral infarction (in Chinese). Journal of Clinical Medical Literature (Electronic Edition) 2018; (19): 166-167.

[4] Li Y, Liu X, Sun Y. Analysis on the diagnostic value of sleep monitoring EEG for patients with epilepsy (in Chinese). Journal of Bingtuan Medicine 2018; (1): 23-24.

[5] Liu W, Chen Z, Wu X, et al. Diagnostic value of video EEG and imaging examination in children with secondary epilepsy (in Chinese). Progress in Modern Biomedicine 2018; (7): 1364-1368.
Published
2020-10-10
Issue
Vol 8 No 3 (2019)
Section
Original Research Article

Copyright (c) 2020 Changmin Ke, Peiping Wang, Chuna Zheng

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