Improved prediction model of seizure risk in children with encephalopathy


  • A prediction model based on clinical risk factors and emergent continuous electroencephalogram (CEEG) risk factors allowed for determination of optimal duration for CEEG for pediatric electroencephalographic seizure (ES) identification.

Why this matters

  • Continuous EEG monitoring is used in children with encephalopathy to measure ES; however, widespread use of CEEG is limited due to resource requirements.

  • Prediction models have identified risk factors to prioritize which children should receive CEEG; however, optimal CEEG durations have not been established. Understanding optimal CEEG durations may lead to improvements in resource requirements, as treatment could be individualized.