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Clinical Outcomes Prediction in Kidney Transplantation by Use of Biomarkers from Hypothermic Machine Perfusion

Overview
Journal Int Braz J Urol
Specialty Urology
Date 2024 May 14
PMID 38743065
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Abstract

Purpose: The clinical outcomes of kidney transplantation from deceased donors have seen significant improvements with the use of machine perfusion (MP), now a standard practice in transplant centers. However, the use of perfusate biomarkers for assessing organ quality remains a subject of debate. Despite this, some centers incorporate them into their decision-making process for donor kidney acceptance. Recent studies have indicated that lactate dehydrogenase (LDH), glutathione S-transferase, interleukin-18, and neutrophil gelatinase-associated lipocalin (NGAL) could predict post-transplant outcomes.

Materials And Methods: Between August 2016 and June 2017, 31 deceased-donor after brain death were included and stroke was the main cause of death. Pediatric patients, hypersensitized recipients were excluded. 43 kidneys were subjected to machine perfusion. Perfusate samples were collected just before the transplantation and stored at -80ºC. Kidney transplant recipients have an average age of 52 years, 34,9% female, with a BMI 24,6±3,7. We employed receiver operating characteristic analysis to investigate associations between these perfusate biomarkers and two key clinical outcomes: delayed graft function and primary non-function.

Results: The incidence of delayed graft function was 23.3% and primary non-function was 14%. A strong association was found between NGAL concentration and DGF (AUC=0.766, 95% CI, P=0.012), and between LDH concentration and PNF (AUC=0.84, 95% CI, P=0.027). Other perfusate biomarkers did not show significant correlations with these clinical outcomes.

Conclusion: The concentrations of NGAL and LDH during machine perfusion could assist transplant physicians in improving the allocation of donated organs and making challenging decisions regarding organ discarding. Further, larger-scale studies are required.

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PMID: 38787513 PMC: 11262721. DOI: 10.1590/S1677-5538.IBJU.2024.04.01.

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