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Dissecting the coma spectrum using Bayesian classification

View ORCID ProfileMartin J. Dietz, Bochra Zareini, Risto Näätänen, Morten Overgaard
doi: https://doi.org/10.1101/832824
Martin J. Dietz
1Center of Functionally Integrative Neuroscience, Institute of Clinical Medicine, Aarhus University, Denmark
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  • For correspondence: martin@cfin.au.dk
Bochra Zareini
1Center of Functionally Integrative Neuroscience, Institute of Clinical Medicine, Aarhus University, Denmark
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Risto Näätänen
1Center of Functionally Integrative Neuroscience, Institute of Clinical Medicine, Aarhus University, Denmark
2Institute of Psychology, University of Tartu, Estonia
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Morten Overgaard
1Center of Functionally Integrative Neuroscience, Institute of Clinical Medicine, Aarhus University, Denmark
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Abstract

A patient who does not regain full consciousness after coma is typically classified as being in a vegetative state or a minimally conscious state. While the key determinants in this differential diagnosis are inferred uniquely from the observed behaviour of the patient, nothing can, in principle, be known about the patient’s awareness of the external world. Given the subjective nature of current diagnostic practice, the quest for neurophysiological markers that could complement the nosology of the coma spectrum is becoming more and more acute. We here present a method for the classification of patients based on electrophysiological responses using Bayesian model selection. We validate the method in a sample of fourteen patients with a clinical disorder of consciousness (DoC) and a control group of fifteen healthy adults. By formally comparing a set of alternative hypotheses about the nosology of DoC patients, the results of our validation study show that we can disambiguate between alternative models of how patients are classified. Although limited to this small sample of patients, this allowed us to assert that there is no evidence of subgroups when looking at the MMN response in this sample of patients. We believe that the methods presented in this article are an important contribution to testing alternative hypotheses about how patients are grouped at both the group and single-patient level and propose that electrophysiological responses, recorded invasively or non-invasively, may be informative for the nosology of the coma spectrum on a par with behavioural diagnosis.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted November 07, 2019.
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Dissecting the coma spectrum using Bayesian classification
Martin J. Dietz, Bochra Zareini, Risto Näätänen, Morten Overgaard
bioRxiv 832824; doi: https://doi.org/10.1101/832824
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Dissecting the coma spectrum using Bayesian classification
Martin J. Dietz, Bochra Zareini, Risto Näätänen, Morten Overgaard
bioRxiv 832824; doi: https://doi.org/10.1101/832824

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