Description

Improved treatment of critically ill patients has resulted in increased patients' survival rates in Intensive Care Units (ICU). This is particularly true for brain injury such as traumatic brain injuries, cerebral hemorrhages or cardiac arrest. While some of these patients regain consciousness after a transient state known as coma, other will develop a prolonged disorder of consciousness (DoC) such as chronic unresponsive wakefulness syndrome (also known as vegetative state) or minimally conscious state, or will remain severely disabled. Consciousness diagnosis and prediction of recovery in DoC currently relies on standardized behavioral assessment and disease-specific markers. However, this strategy may fail to detect covert consciousness due to major sensory and motor deficits. Moreover, the DoC etiology and pathophysiology are heterogenous and most likely result from the combination of factors whose interplay still needs to be clarified. Consciousness detection in DoC is of great importance in term of medical management (e.g., pain management, communication), prognosis (e.g., orientation to adapted rehabilitation center to maximize chance of recovery) and end-of-life discussions (e.g., withholding and/or withdrawing of life support discussion). Furthermore, taking care of these patients can be very stressful due to the high levels of uncertainty associated to their potential of recovery. For all these reasons it is critical to develop personalized diagnosis and prognosis assessment tools that can allow better decisions.

The M-NeuroDoC study will take advantage from the state-of-the-art multimodal assessment ongoing at our institution for both acute and chronic patients in order to improve recovery prediction.

Indeed, our multimodal assessment practice constitutes a great and unique opportunity to better understand the respective diagnostic and prognostic accuracy performances of markers such as behavioral, electrophysiological and neuroimaging that are routinely performed at our institution.

The overall outcome of this project will allow to draw better single-patient predictions of state, prognosis, and rehabilitation strategies and furthermore, a better understanding the pathophysiological mechanisms behind DoC that could result in groundbreaking new personalized therapeutic approaches.

Based on the collected data, we will evaluate the respective diagnostic accuracy of all the markers acquired in clinical practice regarding the clinical outcome at 2 years.

Data of interest will be:

• repeated neurological assessments
• repeated behavioural assessments suing validated tools:
• neurophysiological explorations
• conventional brain imagery (CT, IRM)
• quantitative brain imagery
• functional brain imagery , mental imagery