Reference : Automated analysis of background EEG and reactivity during therapeutic hypothermia in...
Scientific journals : Article
Engineering, computing & technology : Multidisciplinary, general & others
http://hdl.handle.net/2268/162456
Automated analysis of background EEG and reactivity during therapeutic hypothermia in comatose patients after cardiac arrest
English
Noirhomme, Quentin mailto [Université de Liège - ULiège > > Centre de recherches du cyclotron >]
Lehembre, Rémy [> >]
Lugo, Zulay [> >]
Lesenfants, Damien [Université de Liège - ULiège > > Centre de recherches du cyclotron >]
Luxen, André mailto [Université de Liège - ULiège > Département de chimie (sciences) > Chimie organique de synthèse >]
Laureys, Steven mailto [Université de Liège - ULiège > > Centre de recherches du cyclotron >]
Oddo, Mauro [> >]
Rossetti, Andrea [> >]
Jan-2014
Clinical EEG and Neuroscience : Official Journal of the EEG and Clinical Neuroscience Society (ENCS)
Yes (verified by ORBi)
International
1550-0594
[en] electroencephalography ; background EEG ; reactivity ; therapeutic hypothermia ; automated analysis
[en] Visual analysis of electroencephalography (EEG) background and reactivity during therapeutic hypothermia provides important outcome information, but is time-consuming and not always consistent between reviewers. Automated EEG analysis may help quantify the brain damage. Forty-six comatose patients in therapeutic hypothermia, after cardiac arrest, were included in the study. EEG background was quantified with burst-suppression ratio (BSR) and approximate entropy, both used to monitor anesthesia. Reactivity was detected through change in the power spectrum of signal before and after stimulation. Automatic results obtained almost perfect agreement (discontinuity) to substantial agreement (background reactivity) with a visual score from EEG-certified neurologists. Burst-suppression ratio was more suited to distinguish continuous EEG background from burst-suppression than approximate entropy in this specific population. Automatic EEG background and reactivity measures were significantly related to good and poor outcome. We conclude that quantitative EEG measurements can provide promising information regarding current state of the patient and clinical outcome, but further work is needed before routine application in a clinical setting.
Centre de Recherches du Cyclotron - CRC
Researchers ; Professionals ; Students
http://hdl.handle.net/2268/162456
also: http://hdl.handle.net/2268/163449
10.1177/1550059413509616

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