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

Eva Korit́áková, Irena Doležalová, Jan Chládek, Tereza Jurková, Jan Chrastina, Filip Plešinger, Robert Roman, Martin Pail, Pavel Jurák, Daniel J. Shaw, Milan Brázdil*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish
Number of pages6
JournalFrontiers in Neuroscience
Publication statusPublished - 11 May 2021

Bibliographical note

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).


  • EEG reactivity
  • efficacy prediction
  • epilepsy
  • epilepsy treatment
  • neurostimulation
  • vagal nerve stimulation


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