Project 447341

The current organ allocation system for liver transplantation (LT) was developed to prioritize the sickest patients and improve equality. However, access to LT has remained compromised among women and other subgroups. The current prioritization system does not adequately serve the changing LT candidate population, where there has been a dramatic increase in non-alcoholic fatty liver disease (NAFLD) and older patients with comorbidities. Organ supply is insufficient to meet the demand, and up to 25% die on the waiting list for LT in Canada. There is an urgent need to revise this prioritization system and make it more equitable. We have confirmed the significant inequalities and dynamics for specific patient subgroups (women, NAFLD, frailty, increasing age, cholestatic liver disease) on the waiting list. Additionally, the evolution in patient clinical characteristics is resulting in a predominance of cancer and cardiac complications after transplant. We have recently developed an Artificial intelligence (AI) algorithm to predict mortality after transplant and personalize patient care. In the proposed project, we will develop a uniquely Canadian framework beyond the MELD Na score using AI for equitable patient prioritization on the waitlist. We will also refine our AI-based algorithm to predict the major complications after LT and provide personalized recommendations for prevention and therapy. Despite a publicly funded health service and a generosity-base organ donation system, there remains an urgent need to reform the current prioritization system, as it is inequitable and results in excessive deaths of specific patient subgroups. We will use Canadian data aligned with new technology to serve patients more equitably on the waiting list and after transplant, and reset survival to normal based on personalized risk profiles.