Multidimensional System to Dynamically Predict Graft Survival After Kidney Transplantation

Completed

Conditions studied: Kidney Transplant Failure

In brief

The incidence of end stage renal disease (ESRD) is rapidly increasing, now affecting an estimated 7.4 million people worldwide. Numerous parameters such as demographic, clinical and functional factors drive the deterioration of the kidney, ultimately leading to ESRD. Although some ESRD prediction models have been derived in the past years, none of these models are dynamic: they do not integrate the repeated measurements recorded throughout individuals' follow-up. As highlighted in several studies, kidney function repeated measurements (i.e., trajectories) are highly associated with graft survival after kidney transplantation. The investigators made the hypothesis that these trajectories may bring relevant information in the context of graft survival risk prediction model. Hence, combining these trajectories with standard graft survival risk factors may enhance prediction performance. This could permit to derive a robust tool that could be updated over time by continuously capturing patient' personal evolution.

Key facts

Study ID
NCT04258891
Run by
Paris Translational Research Center for Organ Transplantation
People needed
14000
Starts
2004-01-01
Expected to finish
2020-06-30
Last updated by the study team
2020-09-16

Who can join

Age: 18 and older. Sex: any. Healthy volunteers: not accepted.

You may qualify if…

You may not qualify if…

Where it is running

Full record on ClinicalTrials.gov

Trial information comes from ClinicalTrials.gov and is refreshed daily. TrialsForMe does not provide medical care and does not run the studies it lists.