Abstracts

Diagnostic Utility of Video Alone in Differentiation of Epileptic Seizures from Paroxysmal Non-epileptic Events in Children

Abstract number : 2.109
Submission category : 4. Clinical Epilepsy / 4B. Clinical Diagnosis
Year : 2022
Submission ID : 2203977
Source : www.aesnet.org
Presentation date : 12/4/2022 12:00:00 PM
Published date : Nov 22, 2022, 05:22 AM

Authors :
Prachi Raichur, – University of Louisville School of Medicine; Tyler Burr, MD – Division of Pediatric Neurology, Norton Children’s Medical Group – University of Louisville; Yosefa Modiano, PhD – Vivian L. Smith Department of Neurosurgery – McGovern Medical School at UT Health; Christopher Barton, MD – Division of Pediatric Neurology, Norton Children’s Medical Group – University of Louisville; Jeetendra Sah, MD – Division of Pediatric Neurology, Norton Children’s Medical Group – University of Louisville; Darren Farber, DO – Division of Pediatric Neurology, Norton Children’s Medical Group – University of Louisville; Dylan Brock, MD – Department of Pediatric Neurology, Norton Children's Medical Group – University of Louisville; Samir Karia, MD – Division of Pediatric Neurology, Norton Children’s Medical Group – University of Louisville; Zulfi Haneef, MBBS, MD – Department of Neurology – Baylor College of Medicine; Cemal Karakas, MD – Division of Pediatric Neurology, Norton Children’s Medical Group – University of Louisville

Rationale: The utilization of video recordings can be a potential tool to view semiologic features and contribute to epilepsy diagnosis and management, especially with the increasing popularity of telehealth appointments during the COVID-19 pandemic. Using video-electroencephalography (v-EEG) diagnosis as a gold standard, we assessed the diagnostic predictive value of videos of habitual events with or without additional clinical data in differentiating the paroxysmal non-epileptic events (PNEE) from epileptic seizures (ES) in children.

Methods: This was a retrospective, single-center, blinded diagnostic accuracy study involving pediatric patients presenting consecutively to the epilepsy monitoring unit (EMU) for characterization of paroxysmal events concerning seizures between June 2020 to December 2020. Four child neurologists blinded to the diagnosis of the patients formulated a diagnostic impression based upon the review of the video alone and video along with supporting clinical information (i.e., demographics, EEG findings, MRI). Features of the video which helped to make a diagnosis were identified by the reviewers as a part of a survey.

Results: A total of 54 patients were included (ES n=24, PNEE n=30). Diagnostic accuracy was calculated for each reviewer and combined across all the ratings. Diagnostic accuracy by video alone was 74.5% with a sensitivity of 80.8%, specificity of 66.7%, a positive predictive value of 75.2%, and a negative predictive value of 73.6% (Table 1). Providing reviewers with clinical information in addition to the videos significantly improved diagnostic accuracy above the videos alone (p=0.008). Inter-rater reliability between four reviewers based on the video alone showed moderate agreement (κ=0.51) and unchanged when additional clinical data was provided (κ=0.51). The ES group was significantly more likely to demonstrate changes in facial expression, generalized stiffening, repetitive eye blinks, and eye deviation, whereas the PNEE group was more likely to display bilateral myoclonic jerking (Table 2).

Conclusions: This study suggests that video recording of prototypical events concerning seizures in children can be accurately classified as PNEE vs. ES by child neurologists based on characteristic semiologic features with moderate inter-rater reliability.

Funding: None of the authors received any financial support for the research, authorship, or publication of this article.
Clinical Epilepsy