Automated EEG entropy measurements in coma, vegetative state/unresponsive wakefulness syndrome and minimally conscious state

Gosseries, Olivia and Schnakers, Caroline and Ledoux, Didier and Vanhaudenhuyse, Audrey and Bruno, Marie-Aurélie and Demertzi, Athéna and Noirhomme, Quentin and Lehembre, Rémy and Damas, Pierre and Goldman, Serge and Peeters, Erika and Moonen, Gustave and Laureys, Steven (2011) Automated EEG entropy measurements in coma, vegetative state/unresponsive wakefulness syndrome and minimally conscious state. Functional Neurology; New Trends in Interventional Neurosciences. , 26 (1). pp. 25-30. ISSN 0393-5264

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Abstract

Monitoring the level of consciousness in brain-injured patients with disorders of consciousness is crucial as it provides diagnostic and prognostic information. Behavioral assessment remains the gold standard for assessing consciousness but previous studies have shown a high rate of misdiagnosis. This study aimed to investigate the usefulness of electroencephalography (EEG) entropy measurements in differentiating unconscious (coma or vegetative) from minimally conscious patients. Left fronto-temporal EEG recordings (10-minute resting state epochs) were prospectively obtained in 56 patients and 16 age-matched healthy volunteers. Patients were assessed in the acute (≤1 month post-injury; n=29) or chronic (>1 month post-injury; n=27) stage. The etiology was traumatic in 23 patients. Automated online EEG entropy calculations (providing an arbitrary value ranging from 0 to 91) were compared with behavioral assessments (Coma Recovery Scale-Revised) and outcome. EEG entropy correlated with Coma Recovery Scale total scores (r=0.49). Mean EEG entropy values were higher in minimally conscious (73±19; mean and standard deviation) than in vegetative/unresponsive wakefulness syndrome patients (45±28). Receiver operating characteristic analysis revealed an entropy cut-off value of 52 differentiating acute unconscious from minimally conscious patients (sensitivity 89% and specificity 90%). In chronic patients, entropy measurements offered no reliable diagnostic information. EEG entropy measurements did not allow prediction of outcome. User-independent time-frequency balanced spectral EEG entropy measurements seem to constitute an interesting diagnostic – albeit not prognostic – tool for assessing neural network complexity in disorders of consciousness in the acute setting. Future studies are needed before using this tool in routine clinical practice, and these should seek to improve automated EEG quantification paradigms in order to reduce the remaining false negative and false positive findings.

Item Type:	Article
Subjects:	600 Tecnologia - Scienze applicate > 610 Medicina e salute (Classificare qui la tecnologia dei servizi medici) > 616 Malattie (classificare qui la Clinica medica, la medicina basata sull'evidenza, la Medicina interna, la Medicina sperimentale) > 616.8 Malattie del sistema nervoso e disturbi mentali (Classificare qui la Neuropsichiatria, la Neurologia)
Depositing User:	Danilo Dezzi
Date Deposited:	30 Sep 2011 14:55
Last Modified:	30 Sep 2011 14:55
URI:	http://eprints.bice.rm.cnr.it/id/eprint/3492

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