期刊
TRANSPLANT IMMUNOLOGY
卷 81, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.trim.2023.101934
关键词
Biomarkers; Reduced graft function; Predictive value; Kidney transplantation; Dysfunction; Rejection
This study found that donor serum TIMP-2 and uNAG levels are useful predictive biomarkers for reduced graft function. They can provide donor-based prediction for RGF.
Background: The study aimed to find predictive biomarkers to evaluate donor kidney function to predict graft dysfunction as well as to assess an early signs of acute graft rejection.Method: Twenty-seven deceased donors and 54 recipients who underwent a successful kidney transplantation were enrolled in the study. An assessment was made in serum and urine from donors and recipients to measure the following biomarkers: neutrophil gelatinase-associated lipocalin (NGAL), kidney injury molecule-1 (KIM-1), tissue inhibitor of metalloproteinase 2 (TIMP-2) and urinary N-acetyl-b-D-glucosaminidase (uNAG). These bio-markers were used to establish a model for predicting a reduced graft function (RGF) classified as either a delayed or slow graft function.Result: Our analysis suggest that out of four tested biomarkers, the serum TIMP-2 and uNAG levels of the donors had a predictive value for RGF; the area under the receiver operating characteristic curves (AUROC) of serum TIMP-2 and uNAG were 0.714 and 0.779, respectively. The combined best fitting prediction model of serum TIMP-2, uNAG, and creatinine levels was better in predicting RGF than the serum creatinine level alone. In addition, the recipient serum TIMP-2 level on the third day post-transplantation (D3) was associated with the estimated glomerular filtration rate (eGFR) on the seventh day post-transplantation (D7; OR 1.119, 95% CI 1.016-1.233, p = 0.022). Furthermore, the ROC curve value revealed that the AUROC of TIMP-2 on D3 was 0.99 (95% CI 0.97-1, p < 0.001), and this was the best predictive value of the renal function on D7.Conclusions: Donor serum TIMP-2 and uNAG levels are useful predictive biomarkers because they can provide the donor-based prediction for RGF.
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