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Related Concept Videos

Epilepsy and Seizures: Overview01:24

Epilepsy and Seizures: Overview

234
Epilepsy is a chronic neurological disease marked by recurrent, unpredictable seizures. These seizures are caused by abnormal electrical discharges in the brain, leading to behavior, sensation, or consciousness alterations. They can also cause transient impairment of awareness, interfering with daily activities.
Various factors can trigger epilepsy, including genetic factors, brain damage, metabolic causes, and unknown etiology. Diagnosis of epilepsy involves electroencephalography (EEG), which...
234

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Related Experiment Video

Updated: Aug 1, 2025

Robotic-Guided Stereoelectroencephalography for Invasive Epilepsy Monitoring
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Automated, machine learning-based alerts increase epilepsy surgery referrals: A randomized controlled trial.

Benjamin D Wissel1, Hansel M Greiner2,3, Tracy A Glauser2,3

  • 1Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA.

Epilepsia
|April 27, 2023
PubMed
Summary
This summary is machine-generated.

Automated electronic alerts significantly increased referrals for epilepsy surgery evaluations in children. This technology may improve access to surgical interventions for epilepsy patients.

Keywords:
clinical decision supportepilepsy surgerymedical informaticsnatural language processingpediatrics

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Area of Science:

  • Neurology
  • Medical Informatics
  • Surgical Outcomes

Background:

  • Epilepsy surgery offers a potential cure for drug-resistant epilepsy.
  • Referral rates for epilepsy surgery evaluations are often suboptimal.
  • Identifying eligible candidates for epilepsy surgery requires specialized clinical assessment.

Purpose of the Study:

  • To evaluate the effectiveness of automated, electronic alerts in increasing referrals for epilepsy surgery.
  • To assess the impact of a clinical decision support system on surgical referrals for pediatric epilepsy patients.

Main Methods:

  • A prospective, randomized controlled trial was conducted across 14 pediatric neurology clinics.
  • A natural language processing-based clinical decision support system within the electronic health record (EHR) screened patients.
  • Potential surgical candidates were randomized to receive an alert or standard care, with referral for neurosurgical evaluation as the primary outcome.

Main Results:

  • Automated alerts significantly increased the likelihood of referral for epilepsy surgery evaluation (9.8% vs. 3.1%).
  • Patients receiving alerts were more than three times as likely to be referred for presurgical evaluation (adjusted HR=3.21).
  • Nine patients (4.4%) in the alert group underwent epilepsy surgery, compared to none in the control group.

Conclusions:

  • Machine learning-based automated alerts can enhance the utilization of referrals for epilepsy surgery evaluations.
  • Implementing clinical decision support systems may improve access to surgical treatment for epilepsy.
  • Automated alerts show promise in optimizing surgical referral pathways for pediatric epilepsy management.