Catherine Duclos, PhD
Postdoctoral Fellow
The Research Institute of the McGill University Health Centre
Montreal, Québec, Canada

Using anesthesia to predict recovery from disorders of consciousness

Loss of consciousness in response to anesthesia is accompanied by specific patterns of brain network reconfiguration. In patients with disorders of consciousness (DOC), who are unable to respond reliably to commands, the presence or absence of these anesthetic-induced reconfiguration patterns may reveal the patient’s underlying capacity for consciousness. Anesthesia may therefore be key to the development of an accurate prognostic measure for acute unresponsive patients. The current study aims to test the accuracy of an entirely new metric for the prognostication of consciousness recovery in coma and DOC – the Adaptive Reconfiguration Index (ARI), which quantifies brain network reconfiguration in response to propofol anesthesia, using high-density (128-channel) electroencephalography (EEG) – and to translate the ARI to a clinical-grade EEG system. Unlike other prognostic measures that rely on global or event-related brain signals, the ARI focuses on resting-state brain signals that are attenuated by the effects of general anesthesia, which putatively include those associated with conscious awareness. Our team has developed a novel within-subject paradigm that assesses brain networks and responses of patients with DOC using themselves as their own controls. The proposed study is both novel and paradigm-shifting, because it introduces anesthesia as a neuromodulation technique to predict consciousness recovery in unresponsive patients in coma and DOC. Indeed, it will test the hypothesis that the brain’s response to propofol can be a marker of potential for consciousness. This study has the potential to situate anesthesia as a prognostic tool for acute care and neurological patients, and to provide healthcare teams with a novel approach to refine patient prognosis. Establishing an accurate prognosis for recovery has major implications for patient treatment decisions, caregivers, and the healthcare system.