How a web-based model helps predict epilepsy risk


Not all children who have seizures are diagnosed with epilepsy, and a definitive diagnosis can be difficult to make. Now, researchers from the Netherlands have developed a Web-based tool to help clinicians predict the probability of future seizures based on early clinical data.

headshot Eric van Diessen, MD, PhD

Eric van Diessen, MD, PhD

Seizures can be scary for parents and children, but researchers from the Netherlands have developed a new model that can help determine the risk of epilepsy and guide future clinical pathways.

For children who have had 1 or more seizures, the model may help to determine the risk a child has of receiving a diagnosis of epilepsy, according to the report. The study, published in Pediatrics, details how the model was developed and tested.1

Epileptic seizures can be underestimated in children because clinical symptoms vary so widely and initial interictal electroencephalogram (EEG) may have limited sensitivity, the report notes.

“Previous efforts have been made to identify prognostic clinical variables for seizure recurrence after first consultation. These studies were restricted to children with a definitive diagnose of epilepsy,” says Eric van Diessen, MD, PhD, of University Medical Center Utrecht, the Netherlands, and lead author of the report. “Diagnosing epilepsy, however, might be difficult considering the heterogeneity of a [first] paroxysmal event in children. Some of these paroxysmal events might not be epileptic in nature. To assist the clinician in the diagnostic workup, with access to an EEG, we developed this prediction model.”

Van Diessen and colleagues developed the model from retrospective data on 451 children that combined clinical data, including age at first seizure and initial EEG findings. The children involved in the study were followed for at least a year and either had been diagnosed with epilepsy or diagnoses were unconfirmed. The model was validated using case data from an additional 187 children.

Forty-five percent of children in the training cohort and 29% in the validation cohort had inconclusive epilepsy diagnoses at the start of the study, according to the report. After a year of follow-up, a definitive diagnosis was made in 94.2% of children in the training cohort and 92% in the validation cohort.

Modeling efforts were considered highly successful, according to the report, and could be used as a screening-but not necessarily diagnostic-tool to assess seizure likelihood and provide insight on when to refer a patient to a specialist.

How the model works

“Our model provides a rational approach to assist clinicians during the diagnostic process by combining routinely available clinical information in a multivariate way,” the researchers write. “More specifically, we expect our model to be useful as an ‘independent’ screening tool to assess the likelihood of a possible seizure to be epileptic in origin and to help the clinician decide on the need for ancillary investigations or refer to an epileptologist.”

The model could be especially useful in children with uncertain diagnoses of epilepsy, as a false diagnosis could result in unnecessary antiepileptic medication use or hospitalizations, the report notes.

“Our prediction tool can help the clinician to decide whether ancillary investigations or referral to an epileptologist are necessary, which is especially preferable for children where the risk is neither high nor low,” says the report. “Additionally, high-risk cases are identified quickly, and appropriate actions can be taken early in the process.”

The research team also made the model available as an Internet application to help clinicians estimate seizure probability in practice.


“To improve the implementation in clinical practice, we constructed a Web application that may assist clinicians to estimate the individualized probability of epilepsy in children who present after 1 or more possible seizures,” van Diessen says. “We do not claim to present a diagnostic tool; obviously, it is up to the clinician to finally conclude whether a child may truly have epilepsy and whether ancillary diagnostics or treatment is indicated.”



1. van Diessen E, Lamberink HJ, Otte WM, et al. A prediction model to determine childhood epilepsy after 1 or more paroxysmal events. Pediatrics. 2018;142(6):e20180931.

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