Expert accuracy and inter-rater agreement of “must-know” EEG findings for adult and child neurology residents

Nascimento FA, Katyal R, Olandoski M, Gao H, Yap S, Matthews R, Rampp S, Tatum W, Strowd R, Beniczky S (2023)

Publication Type: Journal article

Publication year: 2023

Journal

Epileptic Disorders John Libbey Eurotext

DOI: 10.1002/epd2.20186

Abstract

Objective: We published a list of “must-know” routine EEG (rEEG) findings for trainees based on expert opinion. Here, we studied the accuracy and inter-rater agreement (IRA) of these “must-know” rEEG findings among international experts. Methods: A previously validated online rEEG examination was disseminated to EEG experts. It consisted of a survey and 30 multiple-choice questions predicated on the previously published “must-know” rEEG findings divided into four domains: normal, abnormal, normal variants, and artifacts. Questions contained de-identified 10–20-s epochs of EEG that were considered unequivocal examples by five EEG experts. Results: The examination was completed by 258 international EEG experts. Overall mean accuracy and IRA (AC1) were 81% and substantial (0.632), respectively. The domain-specific mean accuracies and IRA were: 76%, moderate (0.558) (normal); 78%, moderate (0.575) (abnormal); 85%, substantial (0.678) (normal variants); 85%, substantial (0.740) (artifacts). Academic experts had a higher accuracy than private practice experts (82% vs. 77%; p =.035). Country-specific overall mean accuracies and IRA were: 92%, almost perfect (0.836) (U.S.); 86%, substantial (0.762) (Brazil); 79%, substantial (0.646) (Italy); and 72%, moderate (0.496) (India). In conclusion, collective expert accuracy and IRA of “must-know” rEEG findings are suboptimal and heterogeneous. Significance: We recommend the development and implementation of pragmatic, accessible, country-specific ways to measure and improve the expert accuracy and IRA.

Authors with CRIS profile

Stefan Rampp Department of Neurosurgery

Involved external institutions

Mayo Clinic Hospital US United States (USA) (US) Washington University in St. Louis US United States (USA) (US) Louisiana State University in Shreveport (LSUS) / Université d'État de louisiane à shreveport US United States (USA) (US) Pontifícia Universidade Católica do Paraná (PUCPR) / Pontifical Catholic University of Paraná BR Brazil (BR) Wake Forest School of Medicine US United States (USA) (US) Veterans Affairs Healthcare System Boston and Harvard Medical School US United States (USA) (US) Emory University US United States (USA) (US) Filadelfia DK Denmark (DK)

How to cite

APA:

Nascimento, F.A., Katyal, R., Olandoski, M., Gao, H., Yap, S., Matthews, R.,... Beniczky, S. (2023). Expert accuracy and inter-rater agreement of “must-know” EEG findings for adult and child neurology residents. Epileptic Disorders. https://doi.org/10.1002/epd2.20186

MLA:

Nascimento, Fábio A., et al. "Expert accuracy and inter-rater agreement of “must-know” EEG findings for adult and child neurology residents." Epileptic Disorders (2023).

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