*Purpose: To evaluate the risk factors for delayed graft function (DGF) in a Brazilian cohort with high DGF incidence, focusing on variables reflecting donor maintenance.

*Methods: Retrospective cohort including deceased donor kidney transplants (KT) performed between Jan/15 and Dec/17 in two Brazilian centers (n=443). Beyond traditional donor/recipient and transplant variables were evaluated and donor maintenance-related (DMR) variables were also included in the model (arterial blood gas pH, serum sodium, blood glucose, urine output, mean arterial pressure, vasopressors use, and reversed cardiac arrest). For predictive multivariable analysis, machine-learning (ML) methods were used, beyond the regression-based models. DGF was defined as the need for dialysis in the first week after KT.

*Results: Most patients (96%) received kidneys from standard criteria donors. DGF incidence was 53%. In multivariable logistic regression analysis, DMR variables did not impact on DGF occurrence. Post-hoc analysis including only KT with cold ischemia time &lt21h (n=220) demonstrated that urine output in 24h prior to recovery surgery (OR 0.639, 95%CI 0.444-0.919) and serum Na+ (OR 1.030, 95%CI 1.052-1.379) were risk factors for DGF. Using ML analysis (decision tree, neural network and support vector machine), urine output mean arterial pressure, ≥ 1 or high dose vasopressors and blood glucose emerged as DGF predictors.

*Conclusions: Variables suggesting poor donor maintenance were associated with DGF, indicating that potential donor care should be optimized to ensure better KT outcomes.

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