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 Davide Trimarchi, Melanie Boly, Olivia Gosseries, Olivier Bodart, Francesco Lo Curto, Cristina Landi, Maurizio Mariotti, Guya Devalle, Steven Laureys, Giulio Tononi, Marcello Massimini
Annals of Neurology September 22, 2016 DOI: 10.1002/ana.24779 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Observational cohort Peer reviewed |
|---|---|
| Sample size | 231 |
| Population | Healthy controls, communicative brain-injured subjects, and noncommunicative patients with disorders of consciousness |
| Keywords | Index typography Stratification seeds World wide web |
| Citations | 504 |
| Key findings | The Perturbational Complexity Index discriminated conscious from unconscious states with 100% sensitivity and specificity in a benchmark population and identified a subset of vegetative state patients with consciousness-compatible brain activity. |
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.