Interrater agreement of classification of photoparoxysmal electroencephalographic response.
Sándor BeniczkyHarald AurlienSilvana FranceschettiAntonio Martins da SilvaFrancesca BisulliCarla BentesCanafoglia LauraLorenzo FerriDavid KrýslAna Rita PeraltaAttila RáczJ Helen CrossAlexis A ArzimanoglouPublished in: Epilepsia (2020)
Our goal was to assess the interrater agreement (IRA) of photoparoxysmal response (PPR) using the classification proposed by a task force of the International League Against Epilepsy (ILAE), and a simplified classification system proposed by our group. In addition, we evaluated IRA of epileptiform discharges (EDs) and the diagnostic significance of the electroencephalographic (EEG) abnormalities. We used EEG recordings from the European Reference Network (EpiCARE) and Standardized Computer-based Organized Reporting of EEG (SCORE). Six raters independently scored EEG recordings from 30 patients. We calculated the agreement coefficient (AC) for each feature. IRA of PPR using the classification proposed by the ILAE task force was only fair (AC = 0.38). This improved to a moderate agreement by using the simplified classification (AC = 0.56; P = .004). IRA of EDs was almost perfect (AC = 0.98), and IRA of scoring the diagnostic significance was moderate (AC = 0.51). Our results suggest that the simplified classification of the PPR is suitable for implementation in clinical practice.
Keyphrases
- deep learning
- machine learning
- functional connectivity
- resting state
- working memory
- end stage renal disease
- clinical practice
- chronic kidney disease
- primary care
- healthcare
- high intensity
- prognostic factors
- computed tomography
- ejection fraction
- magnetic resonance imaging
- emergency department
- quality improvement
- drug induced
- neural network