Prospective validation study of an epilepsy seizure risk system for outpatient evaluation.

ABSTRACT:

Objective

We conducted clinical testing of an automated Bayesian machine learning algorithm (Epilepsy Seizure Assessment Tool [EpiSAT]) for outpatient seizure risk assessment using seizure counting data, and validated performance against specialized epilepsy clinician experts.

Methods

We conducted a prospective longitudinal study of EpiSAT performance against 24 specialized clinician experts at three tertiary referral epilepsy centers in the United States. Accuracy, interrater reliability, and intra-rater reliability of EpiSAT for correctly identifying changes in seizure risk (improvements, worsening, or no change) were evaluated using 120 seizures from four synthetic seizure diaries (seizure risk known) and 120 seizures from four real seizure diaries (seizure risk unknown).

SUBMITTER: Chiang S 

PROVIDER: S-EPMC6980278 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature