Year: 2026
Type: article
Study design: Observational Study
Abstract: Background: Incidence of delayed graft function (DGF) increases due to the decline in donor kidney quality and the increased use of marginal allografts, while the promising biomarkers for early DGF prediction are lacking. Previous analyses showed that Tenascin-C (TNC) was associated with acute kidney injury; however, its correlation with DGF is unclear. This study aimed to evaluate the ability of TNC to predict DGF. Methods: This prospective study included 36 perioperative kidney transplant recipients. Serum and urine samples were collected at regular intervals before and during the 10 days after transplantation to measure TNC and other conventional biomarkers. Pre-implantation graft renal biopsies were analyzed using Remuzzi and TNC staining scores. These data were then combined with clinical risk factors to construct a DGF prediction model. Results: In recipients with DGF, sTNC levels peaked on postoperative day 4, and were associated with increased risk of composite events (DGF and rehospitalization). uTNC levels were significantly higher in recipients without DGF, peaking at 8 hours postoperatively. sTNC levels at postoperative day 4 and TNC immunohistochemical scores were identified as independent risk factors for DGF. Incorporating the above two factors into a model comprising recipient age, cholesterol levels, donor cold ischemia time, and surgery duration significantly improved its ability to predict DGF, with the area under the curve increasing from 0.6790 to 0.9321. Conclusion: This study highlights the TNC levels in perioperative kidney transplant recipients and their correlation with DGF. sTNC levels and TNC immunohistochemical staining scores may serve as potential biomarker predicting DGF.
Source: Frontiers in Immunology
Institutions: Nanfang Hospital, Southern Medical University
Language: English
Subfield: Transplantation
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,801
Award: G3581993290
OpenAlex ID: W7129768609
