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Development of an Innovative Clinico-biological Score for the Early Detection of Acute Renal Failure Associated With Cardiac Surgery.

Nantes University Hospital · 2022
ClinicalTrials.gov · Datasets · License: Public Domain · 2022
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acute-kidney-injury
The prediction and early detection of acute renal failure associated with cardiac surgery (ARF-CS) are desirable in order to try to reduce its magnitude. Indeed, its incidence is high (29 to 36%, reaching up to 81% in some series, depending on the vulnerability of the target population) and its consequences are often serious: prolongation of the length of stay in the intensive care unit and in hospital, death, and evolution towards chronic renal failure, possibly end-stage (justifying long-term extra-renal purification and/or renal transplantation). The challenge is all the more crucial given the high volume of cardiac surgery. In this context, the objective of identifying early on patients at high risk of developing AKI-CC - and therefore eligible for "nephroprotective" measures has generated, in the last decade, a strong interrest around preoperative scores and biomarkers. Thus, more than ten models predicting AKI-CC have been developed and more than 150 candidate biomarkers have been identified since 2004. This insterest is not waning. The DETECT-AKI project aims to evaluate, in a large population (N=400 patients) with varied patient profiles, not only the performance of the most innovative and promising preoperative scores and biomarkers described in the literature, but also the combination of biomarkers with relevant perioperative clinical and biological data in the framework of a clinico-biological score for the early identification of AKI-CC
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