Background Hypothermic machine perfusion (HMP) is increasingly being used in cardiac death kidney transplantation, but the value of assessing organ quality and predicting DGF through HMP parameters is still controversial.

Methods Three hundred sixty-six qualified kidneys were randomly assigned to the development and validation cohorts in a 2:1 distribution. The HMP variables of the development cohort were used as candidate univariate predictors for DGF. Then, the independent predictors of DGF were identified by multivariate logistic regression analysis with a p value <0.05.According to the OR values, each HMP variable was given a weighted integer and the sum of the integers was a total risk score for each kidney.

Results HMP duration, resistanceand flow rate were identified as independent predictors of DGF. The HMP predictive scores ranged from 0 to 14, and there was a clear increase in the incidence of DGF moving from the low to very-high predictive score group. According to the frequency associated with different risk scores of DGF, we formed four increasingly serious risk categories (scores 0–3, 4–7, 8–11, and 12–14). The HMP predictive scores demonstrated good discriminative power with a c-statistic of 0.706 in the validation cohort, and significantly better prediction value for DGF than terminal flow and resistance (p<0.05).

Conclusion The HMP predictive score is a good noninvasive tool for assessing the quality of DCD kidneys, and is potentially useful for physicians in making optimal decisions about donor organ offers.

CITATION INFORMATION: Ding C., Xue W., Tian P., Ding X., Pan X., Xiang H., Li Y., Tian X., Han F., Tai Q. Predictive Scores for Delayed Graft Function Based on Hypothermic Machine Perfusion Variables in Kidney Transplantation Am J Transplant. 2017;17 (suppl 3).

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