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Quantitative description of the state of awareness of patients in vegetative and minimally conscious state


Wieser, M; Buetler, L; Koenig, A; Riener, R (2010). Quantitative description of the state of awareness of patients in vegetative and minimally conscious state. IEEE Engineering in Medicine and Biology Magazine, (1):5533-5536.

Abstract

Clinical scales represent the golden standard in characterizing awareness for patients in vegetative or in a minimally conscious state. Clinical scales suffer from problems of sensitivity, specificity, subjectivity, and inter-rater reliability. This leads to a misdiagnosis rate of up to 40% and consequences associated with inappropriate treatment decisions. In this study, objective measures including physiological and neurological signals are used to quantify the patient status. Using linear backward regression analysis, 13 variables (based on frequency analysis of the electrocardiogram, heart rate variability, amplitude and latency of the P300, skin conductance responses, changes in the blood pressure and respiration signal) were found to be sufficient to describe 74.7% of the variability of the scores. In this regression model, the P300, electrocardiogram and the blood pressure signal account for most of the variability. More patient data and additional measures will enable refinement of the methods. This new objective-measurement based model of the state of awareness will complement the clinical scales in order to increase the quality of diagnosis.

Abstract

Clinical scales represent the golden standard in characterizing awareness for patients in vegetative or in a minimally conscious state. Clinical scales suffer from problems of sensitivity, specificity, subjectivity, and inter-rater reliability. This leads to a misdiagnosis rate of up to 40% and consequences associated with inappropriate treatment decisions. In this study, objective measures including physiological and neurological signals are used to quantify the patient status. Using linear backward regression analysis, 13 variables (based on frequency analysis of the electrocardiogram, heart rate variability, amplitude and latency of the P300, skin conductance responses, changes in the blood pressure and respiration signal) were found to be sufficient to describe 74.7% of the variability of the scores. In this regression model, the P300, electrocardiogram and the blood pressure signal account for most of the variability. More patient data and additional measures will enable refinement of the methods. This new objective-measurement based model of the state of awareness will complement the clinical scales in order to increase the quality of diagnosis.

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Additional indexing

Other titles:32nd Annual International Conference of the IEEE EMBS Buenos Aires, Argentina, August 31 - September 4, 2010
Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > Balgrist University Hospital, Swiss Spinal Cord Injury Center
Dewey Decimal Classification:610 Medicine & health
Language:English
Date:2010
Deposited On:31 Jan 2011 13:30
Last Modified:05 Apr 2016 14:41
Publisher:IEEE
ISSN:0739-5175
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1109/IEMBS.2010.5626763
PubMed ID:21096471

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