Prediction begins with diagnosis: Estimating seizure recurrence risk in the First Seizure Clinic

Abstract

Objectives: To assess the feasibility of using a seizure recurrence prediction tool in a First Seizure Clinic, considering (1) the accuracy of initial clinical diagnoses and (2) performance of automated computational models in predicting seizure recurrence after first unprovoked seizure (FUS). Methods: To assess diagnostic accuracy, we analysed all sustained and revised diagnoses in patients seen at a First Seizure Clinic over 5 years with 6+ months follow-up (‘accuracy cohort’, n = 487). To estimate prediction of 12-month seizure recurrence after FUS, we used a logistic regression of clinical factors on a multicentre FUS cohort (‘prediction cohort’, n = 181), and compared performance to a r..