Přehled o publikaci
2023
Entropy in scalp EEG can be used as a preimplantation marker for VNS efficacy
SKLENÁROVÁ, Barbora; Jan CHLÁDEK; M. MACEK; Milan BRÁZDIL; Jan CHRASTINA et. al.Basic information
Original name
Entropy in scalp EEG can be used as a preimplantation marker for VNS efficacy
Authors
SKLENÁROVÁ, Barbora (703 Slovakia, belonging to the institution); Jan CHLÁDEK (203 Czech Republic, belonging to the institution); M. MACEK (203 Czech Republic); Milan BRÁZDIL (203 Czech Republic, belonging to the institution); Jan CHRASTINA (203 Czech Republic, belonging to the institution); Tereza JURKOVÁ (203 Czech Republic, belonging to the institution); Petra BÚŘILOVÁ (203 Czech Republic, belonging to the institution); F. PLESINGER (203 Czech Republic); Eva ZATLOUKALOVÁ (203 Czech Republic, belonging to the institution) and Irena DOLEŽALOVÁ (203 Czech Republic, guarantor, belonging to the institution)
Edition
SCIENTIFIC REPORTS, England, NATURE PORTFOLIO, 2023, 2045-2322
Other information
Language
English
Type of outcome
Article in a journal
Country of publisher
Germany
Confidentiality degree
is not subject to a state or trade secret
References:
RIV identification code
RIV/00216224:14110/23:00132842
Organization
Lékařská fakulta – Repository – Repository
UT WoS
001105087400032
EID Scopus
2-s2.0-85175736015
Keywords in English
Epilepsy; Neurological disorders; Neurology; Neuroscience
Links
LX22NPO5107, research and development project. CZECRIN IV, large research infrastructures.
Changed: 22/8/2024 00:50, RNDr. Daniel Jakubík
Abstract
V originále
lt; 50%. Our work aims to differentiate between these two patient groups in preimplantation EEG analysis by employing several Entropy methods. We identified 59 drug-resistant epilepsy patients treated with VNS. We established their response to VNS in terms of responders and non-responders. A preimplantation EEG with eyes open/closed, photic stimulation, and hyperventilation was found for each patient. The EEG was segmented into eight time intervals within four standard frequency bands. In all, 32 EEG segments were obtained. Seven Entropy methods were calculated for all segments. Subsequently, VNS responders and non-responders were compared using individual Entropy methods. VNS responders and non-responders differed significantly in all Entropy methods except Approximate Entropy. Spectral Entropy revealed the highest number of EEG segments differentiating between responders and non-responders. The most useful frequency band distinguishing responders and non-responders was the alpha frequency, and the most helpful time interval was hyperventilation and rest 4 (the end of EEG recording).
