Project 463027

Advances in life-saving medical technology have dramatically increased survival rates amongst those in industrialized countries that sustain a severe brain injury. These individuals typically require hospitalization in intensive care units (ICUs), where critical treatment decisions are made to maximize their likelihood of recovering consciousness and cognitive function. These early treatment decisions are typically based on the unreliable behavioural responses of the patient - which are highly dependent on a multitude of clinical and environmental factors - rather than on objective and quantifiable markers. Consequently, there is a critical need to develop systems and techniques that can be deployed at the bedside to predict patient outcome, and thus inform clinical decision-making. Our team has recently shown that the brain's response to an anesthetic can predict recovery of consciousness in unresponsive, brain-injured patients. As removal of anesthetic drugs for clinical assessment occurs frequently in the ICU, we aim to translate our previous results to this common clinical practice to predict consciousness and cognitive recovery. To this end, we will develop a point-of-care index that can accurately predict patient outcomes within the first week of ICU admission. This index will use advanced techniques in brain network analysis using high-density electroencephalography, combined with an online, patient-accessible battery of cognitive tests for long-term assessment of cognitive function in brain injury survivors. This study has the potential to transform our understanding of the brain mechanisms underlying consciousness and cognition by identifying the key networks associated with their recovery. Results will have a profound and direct impact on the clinical assessment and care of brain-injured ICU patients, and will drive efforts to develop targeted interventions to facilitate recovery and quality of life after serious brain injury.