This cohort study evaluated 200 patients who underwent kidney transplantation between May 2021 and January 2024. The study compared an infection group (130 cases) to an infection-free group (70 cases) to assess the predictive value of Th17/Treg cells and specific cytokine levels, including IL-17, IL-22, IL-10, and TGF-β, within 1 year post-surgery.
Results indicated that the infection group had a higher age and a higher proportion of preoperative hemodialysis compared to the non-infection group (p < 0.05). Regarding cellular and cytokine profiles, the infection group demonstrated higher Th17 cell proportions, higher Th17/Treg ratios, and higher serum IL-17 and IL-22 levels. Conversely, Treg cell proportions and serum IL-10 and TGF-β levels were lower in the infection group (p < 0.001).
Analysis identified preoperative hemodialysis, elevated Th17/Treg ratio, elevated IL-17 and IL-22 levels, and reduced IL-10 and TGF-β levels as independent risk factors for infection (p < 0.05). The Th17/Treg ratio demonstrated a high predictive value for infection within 1 year post-surgery, with an AUC of 0.927.
Safety and adverse event data were not reported. While these cytokine levels and cell ratios may serve as potential biomarkers for early clinical assessment of infection risk, this study identifies associations and does not establish direct causation.
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ObjectiveThis study aimed to analyze the factors associated with infection after kidney transplantation and to explore the predictive value of Th17/Treg cells and cytokine levels for infection.MethodsA retrospective analysis was conducted on 200 patients who underwent kidney transplantation between May 2021 and January 2024. Patients were divided into an infection-free group (70 cases) and an infection group (130 cases) based on infection status within 1 year post-surgery. General clinical data were collected, and changes in Th17 and Treg cell ratios were detected using flow cytometry. Cytokine levels, including IL-17, IL-22, IL-10, and TGF-β, were measured using an enzyme-linked immunosorbent assay (ELISA) kit. Patients were divided into high- and low-expression groups based on the median serum Th17/Treg cell and cytokine levels, and the incidence of infection after kidney transplantation was compared between the two groups. Logistic regression analysis was used to identify independent risk factors for infection after kidney transplantation. Receiver operating characteristic (ROC) curve analysis was performed to assess the predictive value of Th17/Treg cell and cytokine levels for infection after kidney transplantation.ResultsThe infection group had a higher age and a higher proportion of preoperative hemodialysis compared to the non-infection group (p < 0.05). The infection group had higher Th17 cell proportions, Th17/Treg ratios, and serum IL-17 and IL-22 levels compared to the non-infection group, while the Treg cell proportions and serum IL-10 and TGF-β levels were lower in the infection group compared to the non-infection group (p < 0.001). High expression of Th17 cells and pro-inflammatory cytokines (IL-17 and IL-22) was associated with an increased risk of infection, while high expression of Treg cells and anti-inflammatory cytokines (IL-10 and TGF-β) was associated with a reduced risk of infection. Multivariate logistic regression analysis indicated that preoperative hemodialysis, elevated Th17/Treg ratio, elevated IL-17 and IL-22 levels, and reduced IL-10 and TGF-β levels were independent risk factors for infection after kidney transplantation (p < 0.05). ROC curve analysis indicated that the aforementioned indicators had high predictive value for infection within 1 year post-surgery, with the Area Under the Curve (AUC) of the Th17/Treg ratio reaching 0.927.ConclusionPatients with post-transplant infections exhibit a significant Th17/Treg cell imbalance. Elevated Th17/Treg ratios, increased IL-17 and IL-22 levels, and decreased IL-10 and TGF-β levels are independent risk factors for post-transplant infections. These indicators also have high predictive value for post-transplant infection risk and may serve as potential biomarkers for early clinical assessment of infection risk.