![]() Combining all these data into one prediction system with the use of artificial intelligence proved successful to lead to a robust integrative tool. Within this context, an international consortium gathering research teams from Europe and the US and led by Professor Alexandre Loupy, head of the Paris Transplant Group, looked at long-term patient data, including a wide variety of patient, donor and graft parameters. So far, no algorithm predicting long-term graft survival has been validated in different countries, populations and clinical scenarios, nor in the setting of randomized controlled trials. ![]() Therefore, implementing such a prediction tool in clinical practice would facilitate therapeutic interventions by guiding clinical decision-making and would also facilitate clinical trials in kidney transplantation. Indeed, over the past 20 years, long-term graft survival did not improve. Food & Drug Administration and the European Medicines Agency, there is a substantial need to develop a robust tool that can predict long-term graft survival. As emphasized by regulatory agencies including the U.S. The survival of kidney transplants is therefore crucial. Unfortunately, due to the lack of available organs, approximately 55% of patients with end-stage renal disease are still treated by dialysis, representing an annual cost of €2.6 billion in France and more than $40 billion in the USA. Renal transplantation is the treatment of choice, offering a better quality of life and survival chances to patients. When it reaches end-stage renal disease and endangers the lives of patients, dialysis or transplantation is required. 21, 2019 /PRNewswire/ - Chronic kidney disease affects 1 out of 10 people worldwide and is steadily increasing.
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