Stratification of unresponsive patients by an independently validated index of brain complexity

Silvia Casarotto, Angela Comanducci, Mario Rosanova, Simone Sarasso, Matteo Fecchio, Martino Napolitani, Andrea Pigorini, Adenauer G. Casali, Pietro D. Trimarchi, Melanie Boly, Olivia Gosseries, Olivier Bodart, Francesco Curto, Cristina Landi, Maurizio Mariotti, Guya Devalle, Steven Laureys, Giulio Tononi, Marcello Massimimi

Research output: Contribution to journalArticle

Abstract

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.

Original languageEnglish
Pages (from-to)718-729
Number of pages12
JournalAnnals of Neurology
Volume80
Issue number5
DOIs
Publication statusPublished - Nov 1 2016

Fingerprint

Persistent Vegetative State
Benchmarking
Consciousness
Brain
Consciousness Disorders
Population
Sensitivity and Specificity
Unconsciousness
Wakefulness
ROC Curve

ASJC Scopus subject areas

  • Neurology
  • Clinical Neurology

Cite this

Casarotto, S., Comanducci, A., Rosanova, M., Sarasso, S., Fecchio, M., Napolitani, M., ... Massimimi, M. (2016). Stratification of unresponsive patients by an independently validated index of brain complexity. Annals of Neurology, 80(5), 718-729. https://doi.org/10.1002/ana.24779

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; Massimimi, Marcello.

In: Annals of Neurology, Vol. 80, No. 5, 01.11.2016, p. 718-729.

Research output: Contribution to journalArticle

Casarotto, S, Comanducci, A, Rosanova, M, Sarasso, S, Fecchio, M, Napolitani, M, Pigorini, A, G. Casali, A, Trimarchi, PD, Boly, M, Gosseries, O, Bodart, O, Curto, F, Landi, C, Mariotti, M, Devalle, G, Laureys, S, Tononi, G & Massimimi, M 2016, 'Stratification of unresponsive patients by an independently validated index of brain complexity', Annals of Neurology, vol. 80, no. 5, pp. 718-729. https://doi.org/10.1002/ana.24779
Casarotto S, Comanducci A, Rosanova M, Sarasso S, Fecchio M, Napolitani M et al. Stratification of unresponsive patients by an independently validated index of brain complexity. Annals of Neurology. 2016 Nov 1;80(5):718-729. https://doi.org/10.1002/ana.24779
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 ; Massimimi, Marcello. / Stratification of unresponsive patients by an independently validated index of brain complexity. In: Annals of Neurology. 2016 ; Vol. 80, No. 5. pp. 718-729.
@article{241e4c6d189244fab9746472d3e53445,
title = "Stratification of unresponsive patients by an independently validated index of brain complexity",
abstract = "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.",
author = "Silvia Casarotto and Angela Comanducci and Mario Rosanova and Simone Sarasso and Matteo Fecchio and Martino Napolitani and Andrea Pigorini and {G. Casali}, Adenauer and Trimarchi, {Pietro D.} and Melanie Boly and Olivia Gosseries and Olivier Bodart and Francesco Curto and Cristina Landi and Maurizio Mariotti and Guya Devalle and Steven Laureys and Giulio Tononi and Marcello Massimimi",
year = "2016",
month = "11",
day = "1",
doi = "10.1002/ana.24779",
language = "English",
volume = "80",
pages = "718--729",
journal = "Annals of Neurology",
issn = "0364-5134",
publisher = "John Wiley and Sons Inc.",
number = "5",

}

TY - JOUR

T1 - Stratification of unresponsive patients by an independently validated index of brain complexity

AU - Casarotto, Silvia

AU - Comanducci, Angela

AU - Rosanova, Mario

AU - Sarasso, Simone

AU - Fecchio, Matteo

AU - Napolitani, Martino

AU - Pigorini, Andrea

AU - G. Casali, Adenauer

AU - Trimarchi, Pietro D.

AU - Boly, Melanie

AU - Gosseries, Olivia

AU - Bodart, Olivier

AU - Curto, Francesco

AU - Landi, Cristina

AU - Mariotti, Maurizio

AU - Devalle, Guya

AU - Laureys, Steven

AU - Tononi, Giulio

AU - Massimimi, Marcello

PY - 2016/11/1

Y1 - 2016/11/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84995784256&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84995784256&partnerID=8YFLogxK

U2 - 10.1002/ana.24779

DO - 10.1002/ana.24779

M3 - Article

AN - SCOPUS:84995784256

VL - 80

SP - 718

EP - 729

JO - Annals of Neurology

JF - Annals of Neurology

SN - 0364-5134

IS - 5

ER -