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Interictal High Frequency Oscillations Detected with Simultaneous Magnetoencephalography and Electroencephalography as Biomarker of Pediatric Epilepsy
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Antiepileptic drug nonadherence predicts pediatric epilepsy seizure outcomes

Avani C Modi1, Yelena P Wu2, Joseph R Rausch2

  • 1From the Division of Behavioral Medicine and Clinical Psychology, Center for Treatment Adherence and Self-Management (A.C.M., Y.P.W.); Division of Behavioral Medicine and Clinical Psychology (J.R.R., J.L.P.); and Division of Neurology (T.A.G.), Cincinnati Children's Hospital Medical Center; and Department of Pediatrics (A.C.M., J.R.R., J.L.P., T.A.G.), University of Cincinnati College of Medicine, Cincinnati, OH. Avani.Modi@cchmc.org.

Neurology
|October 31, 2014
PubMed

Insights

Predicting long-term seizure outcomes in children with epilepsy is possible through adherence patterns and biological factors. Early interventions for antiepileptic drug (AED) adherence can improve seizure control.

Area of Science:

  • Pediatric Neurology
  • Epileptology
  • Clinical Pharmacy

Background:

  • Long-term seizure outcomes in children with epilepsy are influenced by various factors.
  • Understanding predictors of seizure control is crucial for effective treatment strategies.

Purpose of the Study:

  • To identify sociodemographic, biological, and antiepileptic drug (AED) adherence predictors of long-term seizure outcomes in pediatric epilepsy.
  • To analyze the relationship between adherence trajectories and seizure probability trajectories.

Main Methods:

  • Prospective, longitudinal, observational study of 109 children with newly diagnosed epilepsy over 2 years.
  • Objective assessment of AED adherence using electronic monitors.
  • Medical chart reviews for seizure outcomes and relevant medical variables.

Main Results:

  • Four adherence trajectory groups and two seizure probability trajectory groups were identified.
  • Recognizable epilepsy syndromes and epileptiform discharges on EEG were significant biological predictors.
  • Adherence trajectory group status significantly predicted seizure trajectory group status (R² = 0.13).

Conclusions:

  • Both adherence patterns and biological epilepsy factors similarly predict longitudinal seizure outcomes.
  • The link between AED nonadherence and seizure outcomes is non-linear.
  • Early interventions to improve AED adherence, especially minimizing variability, may alter seizure trajectories.
Abstract

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