Prediction of vagal nerve stimulation efficacy - validation of statistic model on external data set, pilot study
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14110%2F20%3A00118615" target="_blank" >RIV/00216224:14110/20:00118615 - isvavai.cz</a>
Výsledek na webu
<a href="https://www.ean.org/fileadmin/user_upload/ean/congress-2020/Present/Abstracts/00_EAN_Journal_2020_Book.pdf" target="_blank" >https://www.ean.org/fileadmin/user_upload/ean/congress-2020/Present/Abstracts/00_EAN_Journal_2020_Book.pdf</a>
DOI - Digital Object Identifier
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Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Prediction of vagal nerve stimulation efficacy - validation of statistic model on external data set, pilot study
Popis výsledku v původním jazyce
Vagal nerve stimulation (VNS) offers a possibility for a substantial seizure reduction in approximately 50% of implanted patients. However, there is a large group of patients who do not profit significantly from this therapy. At the moment, there is no widelyaccepted method for prediction of VNS efficacy based on pre-implantation data. Our group has developed and published a statistic classifier based on pre-implantation routine EEG, which was able to predict VNS response in a given patient with high accuracy. The crucial limitation of our previous work was its monocentric nature and the use of only one type of EEG recording system.
Název v anglickém jazyce
Prediction of vagal nerve stimulation efficacy - validation of statistic model on external data set, pilot study
Popis výsledku anglicky
Vagal nerve stimulation (VNS) offers a possibility for a substantial seizure reduction in approximately 50% of implanted patients. However, there is a large group of patients who do not profit significantly from this therapy. At the moment, there is no widelyaccepted method for prediction of VNS efficacy based on pre-implantation data. Our group has developed and published a statistic classifier based on pre-implantation routine EEG, which was able to predict VNS response in a given patient with high accuracy. The crucial limitation of our previous work was its monocentric nature and the use of only one type of EEG recording system.
Klasifikace
Druh
O - Ostatní výsledky
CEP obor
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OECD FORD obor
30103 - Neurosciences (including psychophysiology)
Návaznosti výsledku
Projekt
<a href="/cs/project/NV19-04-00343" target="_blank" >NV19-04-00343: Predikce Efektu Stimulace u pacientů s Epilepsií (PRESEnCE)</a><br>
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Ostatní
Rok uplatnění
2020
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů