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Serum uric acid as a risk factor for rejection after deceased donor kidney transplantation: A mono-institutional analysis of paired kidneys

BACKGROUND: Deceased donor kidney transplantation (DDKT) is a major therapeutic option for patients with end-stage renal diseases. Although medical techniques improved in recent years, acute or chronic rejection after DDKT is not uncommon and often results in poor graft survival. Therefore, the dete...

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Detalles Bibliográficos
Autores principales: Zhang, Fuxun, Liang, Jiayu, Xiong, Yang, Zhang, Fan, Wu, Kan, Wang, Wei, Yuan, Jiuhong, Lin, Tao, Wang, Xianding
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9791182/
https://www.ncbi.nlm.nih.gov/pubmed/36578496
http://dx.doi.org/10.3389/fimmu.2022.973425
Descripción
Sumario:BACKGROUND: Deceased donor kidney transplantation (DDKT) is a major therapeutic option for patients with end-stage renal diseases. Although medical techniques improved in recent years, acute or chronic rejection after DDKT is not uncommon and often results in poor graft survival. Therefore, the determination of risk factors is very important to stratify patients and to improve outcomes. This study aims to evaluate the risk factors for treated rejection (TR) of patients after DDKT. METHODS: Clinical data of deceased donors and corresponding recipients were retrospectively collected. The primary outcome was TR defined as the treatment for rejection within 24 months after DDKT. Univariate comparisons of baseline characteristics were performed with Chi-square test, t-test, and Mann–Whitney U test. Logistic regression was constructed to analyze potential risk factors. Receiver operating characteristic (ROC) curve and Jordan index were generated to determine the optimal cutoff value. The association between continuous variables and TR was examined and visualized by using restricted cubic spline (RCS) models. RESULTS: Data of 123 deceased donors and 246 recipients were obtained and analyzed. The median age was 41 (4–62) years for recipients and 39 (1–65) years for donors. The recipients who died or suffered graft loss during the follow-up period were 8 (3.3%) and 12 (4.9%), respectively. After univariate analysis and subsequent multivariate analysis, the preoperative serum uric acid (OR, 2.242; 95% CI, 1.037–4.844; P = 0.040), platelet (OR, 2.163; 95% CI, 1.073–4.361, P = 0.031), absolute neutrophil count (OR, 2.183; 95% CI, 1.025–4.649; P = 0.043), and HLA-DQ mismatch (OR, 2.102; 95% CI, 1.093–4.043; P = 0.026) showed statistical significance. RCS models showed that patients with higher levels of uric acid had increased risk of TR. CONCLUSIONS: Serum uric acid and other three indicators were found to be the independent risk factors for TR, which may contribute to stratify patients and develop personalized regimen in perioperative period.