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A randomized controlled educational pilot trial of interictal epileptiform discharge identification for neurology residents.
Nascimento, Fábio A; Jing, Jin; Traner, Christopher; Kong, Wan Yee; Olandoski, Marcia; Kapur, Srishti; Duhaime, Erik; Strowd, Roy; Moeller, Jeremy; Westover, M Brandon.
Afiliación
  • Nascimento FA; Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.
  • Jing J; Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA.
  • Traner C; Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.
  • Kong WY; Department of Neurology, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA.
  • Olandoski M; Department of Neurology, Yale School of Medicine, New Haven, Connecticut, USA.
  • Kapur S; Department of Neurology, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA.
  • Duhaime E; School of Medicine, Pontifícia Universidade Católica Do Paraná, Curitiba, Brazil.
  • Strowd R; Centaur Labs, Boston, Massachusetts, USA.
  • Moeller J; Centaur Labs, Boston, Massachusetts, USA.
  • Westover MB; Department of Neurology, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA.
Epileptic Disord ; 26(4): 444-459, 2024 Aug.
Article en En | MEDLINE | ID: mdl-38669007
ABSTRACT

OBJECTIVE:

To assess the effectiveness of an educational program leveraging technology-enhanced learning and retrieval practice to teach trainees how to correctly identify interictal epileptiform discharges (IEDs).

METHODS:

This was a bi-institutional prospective randomized controlled educational trial involving junior neurology residents. The intervention consisted of three video tutorials focused on the six IFCN criteria for IED identification and rating 500 candidate IEDs with instant feedback either on a web browser (intervention 1) or an iOS app (intervention 2). The control group underwent no educational intervention ("inactive control"). All residents completed a survey and a test at the onset and offset of the study. Performance metrics were calculated for each participant.

RESULTS:

Twenty-one residents completed the study control (n = 8); intervention 1 (n = 6); intervention 2 (n = 7). All but two had no prior EEG experience. Intervention 1 residents improved from baseline (mean) in multiple metrics including AUC (.74; .85; p < .05), sensitivity (.53; .75; p < .05), and level of confidence (LOC) in identifying IEDs/committing patients to therapy (1.33; 2.33; p < .05). Intervention 2 residents improved in multiple metrics including AUC (.81; .86; p < .05) and LOC in identifying IEDs (2.00; 3.14; p < .05) and spike-wave discharges (2.00; 3.14; p < .05). Controls had no significant improvements in any measure.

SIGNIFICANCE:

This program led to significant subjective and objective improvements in IED identification. Rating candidate IEDs with instant feedback on a web browser (intervention 1) generated greater objective improvement in comparison to rating candidate IEDs on an iOS app (intervention 2). This program can complement trainee education concerning IED identification.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Electroencefalografía / Internado y Residencia / Neurología Límite: Adult / Female / Humans / Male 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 / Internado y Residencia / Neurología Límite: Adult / Female / Humans / Male Idioma: En Revista: Epileptic Disord Asunto de la revista: CEREBRO / NEUROLOGIA Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos