Predictive Score Model for Delayed Graft Function Based on Easily Available Variables before Kidney Donation after...

Area of Science:

• Nephrology
• Transplantation Medicine
• Medical Informatics

Background:

• Evaluating kidney quality from donation after cardiac death (DCD) donors is crucial for transplantation success in China.
• A simple donor risk score model was developed to assess DCD kidney quality pre-donation.

Purpose of the Study:

• To develop and validate a simple donor risk score for assessing the quality of donation after cardiac death (DCD) kidneys.
• To aid physicians in making informed decisions regarding DCD organ offers.

Main Methods:

• 543 kidneys were randomized into development (2:1) and validation cohorts.
• Donor variables were analyzed for prediction of delayed graft function (DGF) using univariate and multivariate logistic regression.
• A donor risk score model was developed and validated using the collected data.

Main Results:

• Eight independent predictors of DGF were identified and assigned weighted scores, creating a risk score from 0 to 28.
• The donor risk score demonstrated good discriminative power (C-statistic 0.790 in development, 0.783 in validation).
• Four risk categories were established based on DGF frequencies related to risk scores.

Conclusions:

• The developed scoring model serves as a valuable noninvasive tool for assessing DCD kidney quality.
• This model can assist physicians in optimizing donor organ offer decisions for kidney transplantation.