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Objective: To determine the duration of epileptic seizure types in patients who did not undergo withdrawal of antiseizure medication.Methods: From a large, structured database of 11 919 consecutive, routine videoelectroencephalograpy (EEG) recordings, labeled using the SCORE (Standardized Computer-Based Organized Reporting of EEG) system, we extracted and analyzed 2742 seizures. For each seizure type we determined median duration and range after removal of outliers (2.5-97.5 percentile). We used surface electromyography (EMG) for accurate measurement of short motor seizures.

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Objective: To develop and validate a pragmatic algorithm that classifies seizure types, to facilitate therapeutic decision-making. Methods: Using a modified Delphi method, five experts developed a pragmatic classification of nine types of epileptic seizures or combinations of seizures that influence choice of medication, and constructed a simple algorithm, freely available on the internet. The algorithm consists of seven ques-K E Y W O R D S algorithm, classification, epilepsy, seizure, web-based application Key Points • We have developed an algorithm that, based on seven questions, classifies seizures for the purpose of drug selection • We have validated the algorithm, implemented in a web-based application (Epipi ck.org), in a prospective, multicenter study on 262 patients • Agreement between the algorithm and the expert classification was 83.2%, with an agreement coefficient .82 (almost perfect agreement)

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