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To further develop personalized medicine in kidney transplantation and improve transplant patient outcomes, attention has been given to define early surrogate endpoints that might aid therapeutic interventions, and help clinical decision-making.
To adequately predict transplant patients' individual risks of allograft loss and patients' complications, this would require a complex integration of data, including: donor data, recipient characteristics, transplant characteristics, biopsies results, immunosuppressive regimen, allograft infections, acute kidney injuries, recipient immune profiles, protocol and per cause biopsies and imaging (PET/CT imaging).
This project aims:
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1,000 participants in 1 patient group
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Laurent Weekers, MD; Antoine Bouquegneau, MD
Data sourced from clinicaltrials.gov
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