EEG Reactivity Predicts Individual Efficacy of Vagal Nerve Stimulation in Intractable Epileptics.

M Brázdil; I Doležalová; E Koritáková; J Chládek; R Roman; M Pail; P Jurák; DJ Shaw; J Chrastina

doi:10.3389/fneur.2019.00392

EEG Reactivity Predicts Individual Efficacy of Vagal Nerve Stimulation in Intractable Epileptics.

M Brázdil, I Doležalová, E Koritáková, J Chládek, R Roman, M Pail, P Jurák, DJ Shaw, J Chrastina

School of Psychology

Research output: Contribution to journal › Article › peer-review

Abstract

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.

Original language	English
Article number	392
Journal	Frontiers in Neurology
Volume	10
DOIs	https://doi.org/10.3389/fneur.2019.00392
Publication status	Published - 2 May 2019

Bibliographical note

© 2019 Brázdil, Doležalová, Koritáková, Chládek, Roman, Pail, Jurák, Shaw and Chrastina. 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.

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10.3389/fneur.2019.00392Licence: CC BY 3.0

fneur-10-00392
© 2019 Brázdil, Doležalová, Koritáková, Chládek, Roman, Pail, Jurák, Shaw and Chrastina. 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.
Final published version, 5.1 MBLicence: CC BY 3.0

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@article{245710574af348de83aab03c3cc0a64c,

title = "EEG Reactivity Predicts Individual Efficacy of Vagal Nerve Stimulation in Intractable Epileptics.",

abstract = "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.",

author = "M Br{\'a}zdil and I Dole{\v z}alov{\'a} and E Korit{\'a}kov{\'a} and J Chl{\'a}dek and R Roman and M Pail and P Jur{\'a}k and DJ Shaw and J Chrastina",

note = " {\textcopyright} 2019 Br{\'a}zdil, Dole{\v z}alov{\'a}, Korit{\'a}kov{\'a}, Chl{\'a}dek, Roman, Pail, Jur{\'a}k, Shaw and Chrastina. 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.",

year = "2019",

month = may,

day = "2",

doi = "10.3389/fneur.2019.00392",

language = "English",

volume = "10",

journal = "Frontiers in Neurology",

publisher = "Frontiers Media S.A.",

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TY - JOUR

T1 - EEG Reactivity Predicts Individual Efficacy of Vagal Nerve Stimulation in Intractable Epileptics.

AU - Brázdil, M

AU - Doležalová, I

AU - Koritáková, E

AU - Chládek, J

AU - Roman, R

AU - Pail, M

AU - Jurák, P

AU - Shaw, DJ

AU - Chrastina, J

N1 - © 2019 Brázdil, Doležalová, Koritáková, Chládek, Roman, Pail, Jurák, Shaw and Chrastina. 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.

PY - 2019/5/2

Y1 - 2019/5/2

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.

AB - 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.

UR - http://europepmc.org/abstract/med/31118916

U2 - 10.3389/fneur.2019.00392

DO - 10.3389/fneur.2019.00392

M3 - Article

C2 - 31118916

VL - 10

JO - Frontiers in Neurology

JF - Frontiers in Neurology

M1 - 392

ER -

EEG Reactivity Predicts Individual Efficacy of Vagal Nerve Stimulation in Intractable Epileptics.

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