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Related Experiment Video

Updated: Sep 17, 2025

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Inter-Rater Reliability of EEG-Based Encephalopathy Grading.

Ryan A Tesh1,2,3, Anika Zahoor1,2,3, Jayme Banks1,2,3

  • 1Department of Neurology, Beth Israel Deaconess Medical Center (BIDMC), Boston, Massachusetts, U.S.A.

Journal of Clinical Neurophysiology : Official Publication of the American Electroencephalographic Society
|July 2, 2025
PubMed
Summary

Experts showed good reliability using the Visual EEG Confusion Assessment Method-Severity (VE-CAM-S) scale for grading encephalopathy. Improvements can be made by refining feature definitions and providing better training examples.

Keywords:
Critical careElectroencephalography (EEG)EncephalopathyPilot studyReliability (inter-rater reliability, IRR)Teaching

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Area of Science:

  • Neurology
  • Neurophysiology
  • Medical Informatics

Background:

  • Encephalopathy severity assessment is crucial for patient management.
  • The Visual EEG Confusion Assessment Method-Severity (VE-CAM-S) is a tool to quantify encephalopathy based on electroencephalography (EEG) features.
  • Evaluating the reliability of VE-CAM-S among experts is essential for its clinical adoption.

Purpose of the Study:

  • To assess the inter-rater reliability of the VE-CAM-S scale among neurological experts.
  • To evaluate the performance of experts in identifying specific EEG features used in VE-CAM-S scoring.
  • To identify common errors in feature recognition that impact VE-CAM-S scores.

Main Methods:

  • Nine experts independently reviewed 32 EEG samples, scoring 29 features (VE-CAM-S and additional).
  • A consensus panel of three experts established the gold standard for scoring.
  • Performance was measured using the Matthews correlation coefficient, sensitivity, and specificity, with qualitative analysis of errors.

Main Results:

  • Experts achieved a median Matthews correlation coefficient of 0.82, indicating good reliability.
  • High specificity (>90%) was observed for most features, but sensitivity varied, with lower scores for burst suppression, EDB, and background rhythms.
  • Common errors included missing subtle findings and misidentifying features like extreme delta brush.

Conclusions:

  • The VE-CAM-S scale demonstrates initial support for reliability in grading encephalopathy.
  • Errors were most significant for high-weight features, suggesting areas for improvement.
  • Recommendations include refining feature definitions, creating visual aids, and enhancing educational materials for better accuracy.