The Success Rate of Neurology Residents in EEG Interpretation After Formal Training


CLINICAL EEG AND NEUROSCIENCE, vol.49, no.2, pp.136-140, 2018 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 49 Issue: 2
  • Publication Date: 2018
  • Doi Number: 10.1177/1550059417736445
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.136-140
  • Hacettepe University Affiliated: Yes


EEG is an important tool for neurologists in both diagnosis and classification of seizures. It is not uncommon in clinical practice to see patients who were erroneously diagnosed as epileptic. Most of the time incorrect interpretation of EEG contributes significantly to this problem. In this study, we aimed to investigate the success rate of neurology residents in EEG interpretation after formal training. Eleven neurology residents were included in the study. Duration of EEG training (3 vs 4 months) and time since completion of EEG education were determined. Residents were randomly presented 30 different slides of representative EEG screenshots. They received 1 point for each correct response. The effect of training duration and time since training were investigated statistically. Besides, we looked at the success rate of each question to see whether certain patterns were more readily recognized than others. EEG training duration (P = .93) and time since completion of training (P = .16) did not influence the results. The success rate of residents for correct responses was between 17% and 50%. On the other hand, the success rate for each question varied between 0% and 91%. Overall, benign variants and focal ictal onset patterns were the most difficult to recognize. On 13 occasions (6.5%) nonepileptiform patterns were thought to represent epileptiform abnormalities. After formal training, neurology residents could identify 50% of the EEG patterns correctly. The wide variation in success rate among residents and also between questions implies that both personal characteristics and inherent EEG features influence successful EEG interpretation.