SP6.8 - Predicting Determinants of Successful Transplantation Using Supra-Marginal (DRI-Donor Risk Index >1.5) Deceased Donor Kidneys

Abstract Objective To develop machine-learning-models with national registry data to predict factors associated with favourable outcomes using supra-marginal ( DRI -Donor Risk Index >1,5) deceased donor kidneys Design A retrospective cohort study using UK Transplant Registry data from 2000-2019 Setting National registry administered by NHS Blood and Transplant in the United Kingdom. Participants Adult recipients (n = 6254) of first kidney-alone transplants from very supra-marginal deceased-donors (DRI≥1.5) Main Outcome Measures Death-censored graft failure and patient mortality Predictors Comprehensive recipient, donor, and transplant characteristics. Statistical Analysis Bayesian neural networks, gradient boosting machines, random forest, and SMOTE-balanced bagging classifiers tuned using Bayesian optimisation Cox regression, competing risk analysis, and calibration plots Results Overall 5-year graft survival was 81%. The random-forest-model had excellent predictive performance for graft failure (AUC 0.88, 95% CI 0.87-0.89; RMSE 0.29). recipient age > 75-years (SHR 1.02, 95% CI 1.01-1.03), recipient-BMI >30 (SHR 1.04, 95% CI 1.02-1.07), HLA mismatches >4 (SHR 1.09, 95% CI 1.01-1.17), donor-creatinine >120mmol/L (SHR 1.002, 95% CI 1.001-1.003), and rejection- within 3-months (SHR 1.56, 95% CI 1.32-1.85) were key determinants of poor survival. Prolonged cold-ischemia-time >14hrs (SHR 1.01, 95% CI 1.007-1.015) was detrimental Conclusions Supra-marginal deceased-donor-kidneys can achieve excellent 5-year outcomes with careful recipient selection. Machine-learning accurately predicted factors associated with success. Adjusted predictors of graft failureVariableSHR95% CIp-valueRecipient-age > 75 years1.021.01-1.03<0.001Recipient-BMI >301.041.02-1.070.002HLA-mismatches >41.091.01-1.170.03Creatinine at offer >120 mmol/L/ 1.4 mg/dl1.0021.001-1.003<0.001Rejection at 3 month1.561.32-1.85<0.001Cold-ischemia-time >14 hrs1.011.007-1.015<0.001SHR: subdistribution hazard ratio;