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During the congress, E-Posters will be accessible to all participants on the congress website 24/7, as well as in the E-poster stations in the congress center.
Preparing your E-Poster
Please review the E-Poster format requirements carefully when preparing your E-Poster. Should your E-Poster not meet the mentioned requirements, it may not be displayed as described above.
E-Poster Submission Deadline
Please prepare and upload your E-Poster no later than March 14, 2026 11.59PM CET. After this date, you will no longer be able to prepare and upload your E-poster and it will not be displayed and accessible on the congress website.
Please follow the instructions below to input your abstract title.
Abstract titles should be brief and reflect the content of the abstract.
Kidney transplantation is the gold-standard treatment for end-stage kidney disease, improving survival, quality of life, and cost-effectiveness. However, graft survival continues to lag behind patient survival, creating increasing demand for retransplantation. While indices such as the Kidney Donor Profile Index (KDPI) and Estimated Post-Transplant Survival (EPTS) score are established for primary transplants, predictors of outcomes after kidney retransplantation remain unclear. In Thailand, the number of retransplantations is rising, but data on prognostic factors are limited. This study aimed to identify clinical and donor-related predictors of graft and patient survival following kidney retransplantation.
We conducted a retrospective cohort study using data from the Thai Transplant Registry (2011–2024). A total of 336 kidney retransplant recipients were included. Multivariable logistic regression was used to identify predictors of patient mortality (N = 217) and graft loss (N = 232) with backward selection. Model performance was assessed using the Hosmer–Lemeshow test and area under the curve (AUC). Survival probabilities were estimated with Kaplan–Meier methods, and independent predictors were confirmed by Cox proportional hazards regression.
Of 336 kidney retransplant recipients, 5 were excluded due to primary non-function, leaving 331 patients for analysis. During follow-up, 55 patients (15.1%) experienced graft loss. Multivariable logistic regressions showed good predictive performance for both patient mortality (AUC = 0.82) and graft loss (AUC = 0.80). Patient mortality was independently associated with donor anti-HBc positivity (AOR 3.20, p = 0.027) and older recipient age (AOR 1.06, p = 0.027). Graft loss was associated with higher discharge serum creatinine (AOR 1.41, p = 0.032) and higher recipient BMI (AOR 1.11, p = 0.028), whereas recipient anti-HBs positivity was protective (AOR 0.34, p = 0.020). Kaplan–Meier analysis showed patient survival probabilities of 0.97, 0.90, and 0.81 at 1, 5, and 10 years, respectively, after retransplantation. In Cox regression, higher discharge creatinine (HR 1.37, p < 0.001), higher recipient BMI (HR 1.06, p= 0.040), older age (HR 1.03, p = 0.006), cerebrovascular disease (HR 4.27, p = 0.020), diabetes (HR 2.67, p = 0.019), donor anti-HBc positivity (HR 2.45, p = 0.019), and donor anti-HIV positivity (HR 7.52, p = 0.049) independently predicted patient mortality. Graft survival probabilities were 0.98, 0.85, and 0.72 at 1, 5, and 10 years, respectively. Predictors of graft loss included older recipient age (HR 1.05, p = 0.002), liver cirrhosis (HR 7.63, p = 0.001), and recipient dyslipidemia (HR 2.09, p = 0.035), while donor anti-CMV IgG positivity was protective (HR 0.29, p = 0.019).
In this national cohort of kidney retransplant recipients, both recipient and donor factors significantly influenced long-term outcomes. Comprehensive metabolic and infectious screening, donor–recipient risk assessment, and optimized peri-discharge management are essential to improve survival after kidney retransplantation.
