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@article{1546030,
author = {Brázdil, Milan and Doležalová, Irena and Koriťáková, Eva and Chládek, Jan and Roman, Robert and Pail, Martin and Jurak, Pavel and Shaw, Daniel Joel and Chrastina, Jan},
article_location = {LAUSANNE},
article_number = {392},
doi = {http://dx.doi.org/10.3389/fneur.2019.00392},
keywords = {vagal nerve stimulation; neurostimulation; epilepsy; efficacy prediction; EEG reactivity; epilepsy treatment},
language = {eng},
issn = {1664-2295},
journal = {FRONTIERS IN NEUROLOGY},
title = {EEG Reactivity Predicts Individual Efficacy of Vagal Nerve Stimulation in Intractable Epileptics},
url = {https://www.frontiersin.org/articles/10.3389/fneur.2019.00392/full},
volume = {10},
year = {2019}
}
TY - JOUR
ID - 1546030
AU - Brázdil, Milan - Doležalová, Irena - Koriťáková, Eva - Chládek, Jan - Roman, Robert - Pail, Martin - Jurak, Pavel - Shaw, Daniel Joel - Chrastina, Jan
PY - 2019
TI - EEG Reactivity Predicts Individual Efficacy of Vagal Nerve Stimulation in Intractable Epileptics
JF - FRONTIERS IN NEUROLOGY
VL - 10
IS - 392
SP - 1-11
EP - 1-11
PB - FRONTIERS MEDIA SA
SN - 16642295
KW - vagal nerve stimulation
KW - neurostimulation
KW - epilepsy
KW - efficacy prediction
KW - EEG reactivity
KW - epilepsy treatment
UR - https://www.frontiersin.org/articles/10.3389/fneur.2019.00392/full
L2 - https://www.frontiersin.org/articles/10.3389/fneur.2019.00392/full
N2 - Background: Chronic vagal nerve stimulation (VNS) is a well-established non-pharmacological treatment option for drug-resistant epilepsy. This study sought to develop a statistical model for prediction of VNS efficacy. We hypothesized that reactivity of the electroencephalogram (EEG) to external stimuli measured during routine preoperative evaluation differs between VNS responders and non-responders. Materials and Methods: Power spectral analyses were computed retrospectively on pre-operative EEG recordings from 60 epileptic patients with VNS. Thirty five responders and 25 non-responders were compared on the relative power values in four standard frequency bands and eight conditions of clinical assessment-eyes opening/closing, photic stimulation, and hyperventilation. Using logistic regression, groups of electrodes within anatomical areas identified as maximally discriminative by n leave-one-out iterations were used to classify patients. The reliability of the predictive model was verified with an independent data-set from 22 additional patients. Results: Power spectral analyses revealed significant differences in EEG reactivity between responders and non-responders; specifically, the dynamics of alpha and gamma activity strongly reflected VNS efficacy. Using individual EEG reactivity to develop and validate a predictive model, we discriminated between responders and non-responders with 86% accuracy, 83% sensitivity, and 90% specificity. Conclusion: We present a new statistical model with which EEG reactivity to external stimuli during routine presurgical evaluation can be seen as a promising avenue for the identification of patients with favorable VNS outcome. This novel method for the prediction of VNS efficacy might represent a breakthrough in the management of drug-resistant epilepsy, with wide-reaching medical and economic implications.
ER -
BRÁZDIL, Milan, Irena DOLEŽALOVÁ, Eva KORIŤÁKOVÁ, Jan CHLÁDEK, Robert ROMAN, Martin PAIL, Pavel JURAK, Daniel Joel SHAW a Jan CHRASTINA. EEG Reactivity Predicts Individual Efficacy of Vagal Nerve Stimulation in Intractable Epileptics. \textit{FRONTIERS IN NEUROLOGY}. LAUSANNE: FRONTIERS MEDIA SA, roč.~10, č.~392, s.~1-11. ISSN~1664-2295. doi:10.3389/fneur.2019.00392. 2019.
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