The challenge of providing an early and accurate diagnosis for a child after an initial paroxysmal event with little information to differentiate epilepsy from other possibilities could become easier with a recently released web-based application.
The model predicts a percentage probability of epilepsy from clinical and electroencephalogram (EEG) data that is routinely available at first consultation, in lieu of or prior to further assessment with such measures as prolonged or sleep-deprived EEG and magnetic resonance imaging (MRI).
The model was developed by Eric van Diessen, MD, PhD, Department of Pediatric Neurology, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, Netherlands, and colleagues, who point out that previous efforts to identify prognostic clinical variables for seizure recurrence have been with studies that have included only children with a definitive diagnosis of epilepsy.