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Related Experiment Video

Updated: Feb 19, 2026

Author Spotlight: Enhancing Graft Viability Assessment Through Quantitative Metrics and Innovative Reservoir Systems
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Prediction of delayed graft function using different scoring algorithms: A single-center experience.

Magda Michalak1, Kristien Wouters2, Erik Fransen3

  • 1Department of Nephrology-Hypertension, Antwerp University Hospital, B-2650 Edegem, Belgium.

World Journal of Transplantation
|November 7, 2017
PubMed
Summary

The Irish delayed graft function (DGF) calculator showed acceptable prediction accuracy in kidney transplant recipients. Other calculators performed poorly, highlighting challenges in external validation of DGF prediction models.

Keywords:
Delayed graft functionKidney transplantationNomogramReceiver operating characteristic curveRisk calculation

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Area of Science:

  • Nephrology
  • Transplant Surgery
  • Medical Informatics

Background:

  • Delayed graft function (DGF) is a significant complication after kidney transplantation.
  • Accurate prediction of DGF risk is crucial for patient management and resource allocation.
  • Several calculators have been developed to predict DGF risk, but their performance in diverse populations requires validation.

Purpose of the Study:

  • To evaluate and compare the predictive performance of three published delayed graft function (DGF) calculators.
  • To assess the accuracy of these calculators in a cohort of deceased donor kidney transplant recipients.

Main Methods:

  • A retrospective analysis of 247 consecutive deceased donor kidney transplants performed between 2003 and 2012.
  • Comparison of observed DGF rates with DGF predictions from three distinct calculators: Irish, Jeldres, and Chapal.
  • Evaluation of calculator accuracy using the c-index (area under the receiver operating characteristic curve).

Main Results:

  • Delayed graft function (DGF) occurred in 15.3% of kidney transplant recipients.
  • The Irish calculator demonstrated acceptable predictive performance (AUC = 0.69), while the Jeldres (AUC = 0.54) and Chapal (AUC = 0.51) calculators showed poor accuracy.
  • Significant differences in calculated DGF risk were observed between DGF-positive and DGF-negative groups (P < 0.0001), but individual patient risk prediction showed wide overlap.

Conclusions:

  • Published predictive models for delayed graft function (DGF) may perform well in their derivation populations but exhibit reduced accuracy upon external validation.
  • The Irish DGF calculator showed promising results in this cohort, suggesting potential utility.
  • Further research is needed to refine and validate DGF prediction tools for broader clinical application.