Grand Total EEG score can differentiate Parkinson's disease from Parkinson-related disorders

Ela Austria Barcelon, Takahiko Mukaino, Jun Yokoyama, Taira Uehara, Katsuya Ogata, Jun ichi Kira, Shozo Tobimatsu

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

Background: Semi-quantitative electroencephalogram (EEG) analysis is easy to perform and has been used to differentiate dementias, as well as idiopathic and vascular Parkinson's disease. Purpose: To study whether a semi-quantitative EEG analysis can aid in distinguishing idiopathic Parkinson's disease (IPD) from atypical parkinsonian disorders (APDs), and furthermore, whether it can help to distinguish between APDs. Materials and Methods: A comprehensive retrospective review of charts was performed to include patients with parkinsonian disorders who had at least one EEG recording available. A modified grand total EEG (GTE) score evaluating the posterior background activity, and diffuse and focal slow wave activities was used in further analyses. Results: We analyzed data from 76 patients with a final diagnosis of either IPD, probable corticobasal degeneration (CBD), multiple system atrophy (MSA), or progressive supra-nuclear palsy (PSP). IPD patients had the lowest mean GTE score, followed those with CBD or MSA, while PSP patients scored the highest. However, none of these differences were statistically significant. A GTE score of ≤9 distinguished IPD patients from those with APD (p < 0.01) with a sensitivity of 100% and a specificity of 33.3%. Conclusion: The modified GTE score can distinguish patients with IPD from those with CBD, PSP or MSA at a cut-off score of 9 with excellent sensitivity but poor specificity. However, this score is not able to distinguish a particular form of APD from other forms of the disorder.

Original languageEnglish
Article number398
JournalFrontiers in Neurology
Volume10
Issue numberAPR
DOIs
Publication statusPublished - 2019

All Science Journal Classification (ASJC) codes

  • Neurology
  • Clinical Neurology

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