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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

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68081731%3A_____%2F21%3A00543276" target="_blank" >RIV/68081731:_____/21:00543276 - isvavai.cz</a>

  • Alternative codes found

    RIV/00159816:_____/21:00074687 RIV/00216224:14110/21:00120112

  • Result on the web

    <a href="https://www.frontiersin.org/articles/10.3389/fnins.2021.635787/full" target="_blank" >https://www.frontiersin.org/articles/10.3389/fnins.2021.635787/full</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.3389/fnins.2021.635787" target="_blank" >10.3389/fnins.2021.635787</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    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

  • Original language description

    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.nObjective: To validate our model using EEG data acquired with a different recording system.nMethods: 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).nResults: The classifier achieved 75% accuracy, 67% sensitivity, and 100% specificity. Only two patients, both real-life responders, were classified incorrectly in both validation experiments.nConclusion: 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.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    30103 - Neurosciences (including psychophysiology)

Result continuities

  • Project

    <a href="/en/project/NV19-04-00343" target="_blank" >NV19-04-00343: Prediction of Stimulation Efficacy in Epilepsy (PRESEnCE)</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2021

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Frontiers in Neuroscience

  • ISSN

    1662-453X

  • e-ISSN

    1662-453X

  • Volume of the periodical

    15

  • Issue of the periodical within the volume

    11 May

  • Country of publishing house

    CH - SWITZERLAND

  • Number of pages

    6

  • Pages from-to

    635787

  • UT code for WoS article

    000653635600001

  • EID of the result in the Scopus database

    2-s2.0-85107209187