Forehead electrodes sufficiently detect propofol-induced slow waves for the assessment of brain function after cardiac arrest.
J Clin Monit Comput
; 34(1): 105-110, 2020 Feb.
Article
en En
| MEDLINE
| ID: mdl-30788811
In a recent study, we proposed a novel method to evaluate hypoxic ischemic encephalopathy (HIE) by assessing propofol-induced changes in the 19-channel electroencephalogram (EEG). The study suggested that patients with HIE are unable to generate EEG slow waves during propofol anesthesia 48 h after cardiac arrest (CA). Since a low number of electrodes would make the method clinically more practical, we now investigated whether our results received with a full EEG cap could be reproduced using only forehead electrodes. Experimental data from comatose post-CA patients (N = 10) were used. EEG was recorded approximately 48 h after CA using 19-channel EEG cap during a controlled propofol exposure. The slow wave activity was calculated separately for all electrodes and four forehead electrodes (Fp1, Fp2, F7, and F8) by determining the low-frequency (< 1 Hz) power of the EEG. HIE was defined by following the patients' recovery for six months. In patients without HIE (N = 6), propofol substantially increased (244 ± 91%, mean ± SD) the slow wave activity in forehead electrodes, whereas the patients with HIE (N = 4) were unable to produce such activity. The results received with forehead electrodes were similar to those of the full EEG cap. With the experimental pilot study data, the forehead electrodes were as capable as the full EEG cap in capturing the effect of HIE on propofol-induced slow wave activity. The finding offers potential in developing a clinically practical method for the early detection of HIE.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Encéfalo
/
Propofol
/
Hipoxia Encefálica
/
Electroencefalografía
/
Paro Cardíaco
Tipo de estudio:
Diagnostic_studies
/
Screening_studies
Límite:
Humans
Idioma:
En
Revista:
J Clin Monit Comput
Asunto de la revista:
INFORMATICA MEDICA
/
MEDICINA
Año:
2020
Tipo del documento:
Article
País de afiliación:
Finlandia