2021
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
KORIŤÁKOVÁ, Eva, Irena DOLEŽALOVÁ, Jan CHLÁDEK, Tereza JURKOVÁ, Jan CHRASTINA et. al.Základní údaje
Originální název
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
Autoři
KORIŤÁKOVÁ, Eva (203 Česká republika, domácí), Irena DOLEŽALOVÁ (203 Česká republika, domácí), Jan CHLÁDEK (203 Česká republika, domácí), Tereza JURKOVÁ (203 Česká republika, domácí), Jan CHRASTINA (203 Česká republika, domácí), Filip PLESINGER (203 Česká republika), Robert ROMAN (203 Česká republika, domácí), Martin PAIL (203 Česká republika, domácí), Pavel JURAK (203 Česká republika), Daniel Joel SHAW (826 Velká Británie a Severní Irsko, domácí) a Milan BRÁZDIL (203 Česká republika, garant, domácí)
Vydání
Frontiers in Neuroscience, Lausanne, Frontiers Media S.A. 2021, 1662-453X
Další údaje
Jazyk
angličtina
Typ výsledku
Článek v odborném periodiku
Obor
30103 Neurosciences
Stát vydavatele
Švýcarsko
Utajení
není předmětem státního či obchodního tajemství
Odkazy
Impakt faktor
Impact factor: 5.152
Kód RIV
RIV/00216224:14110/21:00120112
Organizační jednotka
Lékařská fakulta
UT WoS
000653635600001
Klíčová slova anglicky
vagal nerve stimulation; neurostimulation; epilepsy; efficacy prediction; EEG reactivity; epilepsy treatment
Příznaky
Mezinárodní význam, Recenzováno
Změněno: 23. 7. 2021 13:54, Mgr. Tereza Miškechová
Anotace
V originále
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.
Návaznosti
NV19-04-00343, projekt VaV |
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