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Expert accuracy and inter-rater agreement of "must-know" EEG findings for adult and child neurology residents.
Nascimento, Fábio A; Katyal, Roohi; Olandoski, Marcia; Gao, Hong; Yap, Samantha; Matthews, Rebecca; Rampp, Stefan; Tatum, William; Strowd, Roy; Beniczky, Sándor.
Afiliación
  • Nascimento FA; Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA.
  • Katyal R; Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.
  • Olandoski M; Department of Neurology, Louisiana State University Health Sciences, Shreveport, Louisiana, USA.
  • Gao H; School of Medicine, Pontifícia Universidade Católica do Paraná, Curitiba, Brazil.
  • Yap S; Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA.
  • Matthews R; Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.
  • Rampp S; Department of Neurology, Emory University School of Medicine, Atlanta, Georgia, USA.
  • Tatum W; Department of Neurosurgery, University Hospital Erlangen, Erlangen, Germany.
  • Strowd R; Department of Neuroradiology, University Hospital Erlangen, Erlangen, Germany.
  • Beniczky S; Department of Neurosurgery, University Hospital Halle (Saale), Halle (Saale), Germany.
Epileptic Disord ; 26(1): 109-120, 2024 Feb.
Article en En | MEDLINE | ID: mdl-38031822
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.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Electroencefalografía / Neurología Límite: Adult / Child / Humans País/Región como asunto: Europa Idioma: En Revista: Epileptic Disord Asunto de la revista: CEREBRO / NEUROLOGIA Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Electroencefalografía / Neurología Límite: Adult / Child / Humans País/Región como asunto: Europa Idioma: En Revista: Epileptic Disord Asunto de la revista: CEREBRO / NEUROLOGIA Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos