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Stratification of unresponsive patients by an independently validated index of brain complexity
OBJECTIVE: Validating objective, brain‐based indices of consciousness in behaviorally unresponsive patients represents a challenge due to the impossibility of obtaining independent evidence through subjective reports. Here we address this problem by first validating a promising metric of consciousne...
Autores principales: | , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5132045/ https://www.ncbi.nlm.nih.gov/pubmed/27717082 http://dx.doi.org/10.1002/ana.24779 |
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author | Casarotto, Silvia Comanducci, Angela Rosanova, Mario Sarasso, Simone Fecchio, Matteo Napolitani, Martino Pigorini, Andrea G. Casali, Adenauer Trimarchi, Pietro D. Boly, Melanie Gosseries, Olivia Bodart, Olivier Curto, Francesco Landi, Cristina Mariotti, Maurizio Devalle, Guya Laureys, Steven Tononi, Giulio Massimini, Marcello |
author_facet | Casarotto, Silvia Comanducci, Angela Rosanova, Mario Sarasso, Simone Fecchio, Matteo Napolitani, Martino Pigorini, Andrea G. Casali, Adenauer Trimarchi, Pietro D. Boly, Melanie Gosseries, Olivia Bodart, Olivier Curto, Francesco Landi, Cristina Mariotti, Maurizio Devalle, Guya Laureys, Steven Tononi, Giulio Massimini, Marcello |
author_sort | Casarotto, Silvia |
collection | PubMed |
description | OBJECTIVE: Validating objective, brain‐based indices of consciousness in behaviorally unresponsive patients represents a challenge due to the impossibility of obtaining independent evidence through subjective reports. Here we address this problem by first validating a promising metric of consciousness—the Perturbational Complexity Index (PCI)—in a benchmark population who could confirm the presence or absence of consciousness through subjective reports, and then applying the same index to patients with disorders of consciousness (DOCs). METHODS: The benchmark population encompassed 150 healthy controls and communicative brain‐injured subjects in various states of conscious wakefulness, disconnected consciousness, and unconsciousness. Receiver operating characteristic curve analysis was performed to define an optimal cutoff for discriminating between the conscious and unconscious conditions. This cutoff was then applied to a cohort of noncommunicative DOC patients (38 in a minimally conscious state [MCS] and 43 in a vegetative state [VS]). RESULTS: We found an empirical cutoff that discriminated with 100% sensitivity and specificity between the conscious and the unconscious conditions in the benchmark population. This cutoff resulted in a sensitivity of 94.7% in detecting MCS and allowed the identification of a number of unresponsive VS patients (9 of 43) with high values of PCI, overlapping with the distribution of the benchmark conscious condition. INTERPRETATION: Given its high sensitivity and specificity in the benchmark and MCS population, PCI offers a reliable, independently validated stratification of unresponsive patients that has important physiopathological and therapeutic implications. In particular, the high‐PCI subgroup of VS patients may retain a capacity for consciousness that is not expressed in behavior. Ann Neurol 2016;80:718–729 |
format | Online Article Text |
id | pubmed-5132045 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-51320452016-12-02 Stratification of unresponsive patients by an independently validated index of brain complexity Casarotto, Silvia Comanducci, Angela Rosanova, Mario Sarasso, Simone Fecchio, Matteo Napolitani, Martino Pigorini, Andrea G. Casali, Adenauer Trimarchi, Pietro D. Boly, Melanie Gosseries, Olivia Bodart, Olivier Curto, Francesco Landi, Cristina Mariotti, Maurizio Devalle, Guya Laureys, Steven Tononi, Giulio Massimini, Marcello Ann Neurol Research Articles OBJECTIVE: Validating objective, brain‐based indices of consciousness in behaviorally unresponsive patients represents a challenge due to the impossibility of obtaining independent evidence through subjective reports. Here we address this problem by first validating a promising metric of consciousness—the Perturbational Complexity Index (PCI)—in a benchmark population who could confirm the presence or absence of consciousness through subjective reports, and then applying the same index to patients with disorders of consciousness (DOCs). METHODS: The benchmark population encompassed 150 healthy controls and communicative brain‐injured subjects in various states of conscious wakefulness, disconnected consciousness, and unconsciousness. Receiver operating characteristic curve analysis was performed to define an optimal cutoff for discriminating between the conscious and unconscious conditions. This cutoff was then applied to a cohort of noncommunicative DOC patients (38 in a minimally conscious state [MCS] and 43 in a vegetative state [VS]). RESULTS: We found an empirical cutoff that discriminated with 100% sensitivity and specificity between the conscious and the unconscious conditions in the benchmark population. This cutoff resulted in a sensitivity of 94.7% in detecting MCS and allowed the identification of a number of unresponsive VS patients (9 of 43) with high values of PCI, overlapping with the distribution of the benchmark conscious condition. INTERPRETATION: Given its high sensitivity and specificity in the benchmark and MCS population, PCI offers a reliable, independently validated stratification of unresponsive patients that has important physiopathological and therapeutic implications. In particular, the high‐PCI subgroup of VS patients may retain a capacity for consciousness that is not expressed in behavior. Ann Neurol 2016;80:718–729 John Wiley and Sons Inc. 2016-11-02 2016-11 /pmc/articles/PMC5132045/ /pubmed/27717082 http://dx.doi.org/10.1002/ana.24779 Text en © 2016 The Authors. Annals of Neurology published by Wiley Periodicals, Inc. on behalf of American Neurological Association. This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial‐NoDerivs (http://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. |
spellingShingle | Research Articles Casarotto, Silvia Comanducci, Angela Rosanova, Mario Sarasso, Simone Fecchio, Matteo Napolitani, Martino Pigorini, Andrea G. Casali, Adenauer Trimarchi, Pietro D. Boly, Melanie Gosseries, Olivia Bodart, Olivier Curto, Francesco Landi, Cristina Mariotti, Maurizio Devalle, Guya Laureys, Steven Tononi, Giulio Massimini, Marcello Stratification of unresponsive patients by an independently validated index of brain complexity |
title | Stratification of unresponsive patients by an independently validated index of brain complexity |
title_full | Stratification of unresponsive patients by an independently validated index of brain complexity |
title_fullStr | Stratification of unresponsive patients by an independently validated index of brain complexity |
title_full_unstemmed | Stratification of unresponsive patients by an independently validated index of brain complexity |
title_short | Stratification of unresponsive patients by an independently validated index of brain complexity |
title_sort | stratification of unresponsive patients by an independently validated index of brain complexity |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5132045/ https://www.ncbi.nlm.nih.gov/pubmed/27717082 http://dx.doi.org/10.1002/ana.24779 |
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