A Novel Statistical Model for Predicting the Efficacy of Vagal Nerve Stimulation in Patients With Epilepsy (Pre-X-Stim) Is Applicable to Different EEG Systems


Background: Identifying patients with intractable epilepsy who would benefit from therapeutic chronic vagal nerve stimulation (VNS) preoperatively remains a major clinical challenge. We have developed a statistical model for predicting VNS efficacy using only routine preimplantation electroencephalogram (EEG) recorded with the TruScan EEG device (Brazdil et al., 2019). It remains to be seen, however, if this model can be applied in different clinical settings. Objective: To validate our model using EEG data acquired with a different recording system. Methods: We identified a validation cohort of eight patients implanted with VNS, whose preimplantation EEG was recorded on the BrainScope device and who underwent the EEG recording according to the protocol. The classifier developed in our earlier work, named Pre-X-Stim, was then employed to classify these patients as predicted responders or non-responders based on the dynamics in EEG power spectra. Predicted and real-world outcomes were compared to establish the applicability of this classifier. In total, two validation experiments were performed using two different validation approaches (single classifier or classifier voting). Results: The classifier achieved 75% accuracy, 67% sensitivity, and 100% specificity. Only two patients, both real-life responders, were classified incorrectly in both validation experiments. Conclusion: We have validated the Pre-X-Stim model on EEGs from a different recording system, which indicates its application under different technical conditions. Our approach, based on preoperative EEG, is easily applied and financially undemanding and presents great potential for real-world clinical use.

Publication DOI: https://doi.org/10.3389/fnins.2021.635787
Divisions: College of Health & Life Sciences > School of Psychology
College of Health & Life Sciences
College of Health & Life Sciences > Aston Institute of Health & Neurodevelopment (AIHN)
Funding Information: This work was supported by the Ministry of Health of the Czech Republic (Grant Number NV19-04-00343).
Additional Information: Copyright © 2021 Korit́áková, Doležalová, Chládek, Jurková, Chrastina, Plešinger, Roman, Pail, Jurák, Shaw and Brázdil. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Funding Information: This work was supported by the Ministry of Health of the Czech Republic (Grant Number NV19-04-00343).
Uncontrolled Keywords: EEG reactivity,efficacy prediction,epilepsy,epilepsy treatment,neurostimulation,vagal nerve stimulation,Neuroscience(all)
Publication ISSN: 1662-4548
Last Modified: 21 Feb 2024 08:50
Date Deposited: 11 Jul 2023 08:06
Full Text Link:
Related URLs: https://www.fro ... 021.635787/full (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2021-05-11
Accepted Date: 2021-03-22
Authors: Korit́áková, Eva
Doležalová, Irena
Chládek, Jan
Jurková, Tereza
Chrastina, Jan
Plešinger, Filip
Roman, Robert
Pail, Martin
Jurák, Pavel
Shaw, Daniel J. (ORCID Profile 0000-0003-1139-8301)
Brázdil, Milan



Version: Published Version

License: Creative Commons Attribution

| Preview

Export / Share Citation


Additional statistics for this record