Absence Seizure Identification by Epileptologists from Guided Hyperventilation Using the Eysz HV Recorder Smartphone Application
Abstract number :
1.518
Submission category :
3. Neurophysiology / 3C. Other Clinical EEG
Year :
2024
Submission ID :
1500
Source :
www.aesnet.org
Presentation date :
12/7/2024 12:00:00 AM
Published date :
Authors :
Presenting Author: Rachel Kuperman, MD – Eysz
Nathaniel Blanco, PhD – Eysz
Gewalin Aungaroon, MD – Cincinnati Children’s Hospital Medical Center
Kelly Kremer, MD – Cincinnati Children’s Hospital Medical Center
Nan Lin, MD – Cincinnati Children’s Hospital Medical Center
Rationale: Childhood Absence Epilepsy (CAE) is the most common childhood epilepsy. Early treatment is critical in CAE, however absence seizures are challenging to identify, leading to diagnostic delays and difficulty measuring treatment efficacy. The gold standard for seizure detection is video EEG (VEEG), but VEEG has to be performed in the hospital, is expensive, and does not enable long-term monitoring. Clinicians may instead rely on self-reports, but patients report only 6% of absence seizures and caregivers report only 14% (Swinnen et al. 2021). There is an urgent need for an accurate tool that can be used outside the clinic to diagnose CAE and monitor treatment responses over time. Hyperventilation (HV) is a reliable, safe method routinely used to provoke absence seizures in clinical settings and elicits seizures in 90% of CAE patients who experience seizures. Additionally, a recent meta-analysis showed that review of videos alone (without EEG) can reliably differentiate epileptic seizures from non-epileptic seizures (Karakas et al. 2023). However, there is no standard protocol for inducing seizures with HV, and the lack of standardization makes it difficult to compare the results of different HV sessions.
Methods: This study tested the efficacy of the Eysz HV Recorder, a smartphone application that guides patients through HV, providing continuous feedback to ensure good effort and standardization. 31 participants underwent guided HV using the Eysz HV Recorder during VEEG observation. Three epileptologists reviewed the VEEG recording and annotated seizure start and stop times. A second set of three epileptologists reviewed the video from the Eysz HV Recorder (with no access to the EEG data) for seizure presence and annotated seizure times. We evaluated the performance of the Eysz HV app reviewers in identifying seizures, using the EEG reviews as the ground truth.
Results: Our study has captured 12 seizures from 6 different participants and recorded 25 participants who did not seize during the recording. Seizures were defined as at least 2 out of 3 VEEG readers marking the same time period as a seizure. Sensitivity of the HV recording video readers was 95% for seizures ≥ 7 s ( two readers having 100% sensitivity), but was lower for seizures that were < 7 s long (Mean: 60%; Fig. 1). Mean specificity across HV app reviewers is 87%. For comparison, we analyzed agreement between the VEEG readers and found a similar result. For events ≥ 7 s there was 100% agreement between all three EEG readers. For events < 7 s, all three reviewers only agreed 50% of the time.
Conclusions: Epileptologists are highly accurate at identifying seizures ≥ 7 s long in videos recorded during guided HV using the Eysz HV Recorder smartphone application. Additionally, HV video readers agreed with the EEG readers at similar rates as EEG readers agree with each other. These results support the use of the Eysz HV Recorder as a screening tool for CAE and a long-term monitoring tool, which could facilitate earlier diagnosis and treatment, improving quality of life.
Funding: NIH SBIR R43NS129363
Neurophysiology