ThermoFisher Scientific Brahms Biomarkers France

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

The purpose of this study is to
Identify a cut-off for the ratio of the serum proteins soluble FMS-like Tyrosine Kinase 1 (sFLT-1) and placental growth factor (PlGF) that identifies women will who develop preeclampsia with severe features within 2 weeks of testing (clinically positive) from those who do not develop preeclampsia with severe features within 2 weeks of testing (clinically negative) among preterm pregnant women with hypertensive disorders of pregnancy.
And
To validate the cut-off the ratio of sFLT-1 and PlGF and to validate the performance of the automated assays used to find the cut-off. Test performance includes positive predictive value, negative predictive value, sensitivity, and specificity.
Subjects will provide blood, urine, and saliva samples at the time of enrollment. Samples will be frozen for batch assessment of sFLT-1 and PlGF levels by automated assays. Clinicians, subjects, and researchers will be blinded to protein level assessment, therefore assay results will not affect clinical management.

This pilot-study will be a prospective, single-centre, observational study including 100 critically ill patients consecutively admitted to the medical intensive care unit (ICU) of the University hospital of Zurich, Switzerland, to assess and validate the use of MR-proADM and the CT-proET1/MR-proADM-ratio as prognostic markers in critically ill patients.