Arthur J Matas1, Erika Helgeson2, Ann Fieberg2, Robert Leduc2, Robert S Gaston3, Bertram L Kasiske4, David Rush5, Lawrence Hunsicker6, Fernando Cosio7, Joseph P Grande8, J Michael Cecka9, John Connett2, Roslyn B Mannon10. 1. Transplantation Division, Department of Surgery, University of Minnesota, Minneapolis, MN. 2. Biostatistics Division, School of Public Health, University of Minnesota, Minneapolis, MN. 3. Department of Medicine, University of Alabama, Birmingham, AL. 4. Division of Nephrology, Hennepin Healthcare, Minneapolis, MN. 5. Department of Internal Medicine, University of Manitoba, Winnipeg, MB, Canada. 6. Department of Internal Medicine, University of Iowa, Iowa City, IA. 7. Division of Nephrology and Hypertension, Department of Internal Medicine, Mayo Clinic, Rochester, MN. 8. Division of Anatomic Pathology, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN. 9. Department of Pathology & Lab Medicine, David Geffen School of Medicine, University of California, UCLA Immunogenetics Center, Los Angeles, CA. 10. University of Nebraska Medical Center and VA Nebraska-Western Iowa Health Care System, Omaha, NE.
Abstract
BACKGROUND: Delayed graft function (DGF) of a kidney transplant results in increased cost and complexity of management. For clinical care or a DGF trial, it would be ideal to accurately predict individual DGF risk and provide preemptive treatment. A calculator developed by Irish et al has been useful for predicting population but not individual risk. METHODS: We analyzed the Irish calculator (IC) in the DeKAF prospective cohort (incidence of DGF = 20.4%) and investigated potential improvements. RESULTS: We found that the predictive performance of the calculator in those meeting Irish inclusion criteria was comparable with that reported by Irish et al. For cohorts excluded by Irish: (a) in pump-perfused kidneys, the IC overestimated DGF risk; (b) in simultaneous pancreas kidney transplants, the DGF risk was exceptionally low. For all 3 cohorts, there was considerable overlap in IC scores between those with and those without DGF. Using a modified definition of DGF-excluding those with single dialysis in the first 24 h posttransplant-we found that the calculator had similar performance as with the traditional DGF definition. Studying whether DGF prediction could be improved, we found that recipient cardiovascular disease was strongly associated with DGF even after accounting for IC-predicted risk. CONCLUSIONS: The IC can be a useful population guide for predicting DGF in the population for which it was intended but has limited scope in expanded populations (SPK, pump) and for individual risk prediction. DGF risk prediction can be improved by inclusion of recipient cardiovascular disease.
BACKGROUND: Delayed graft function (DGF) of a kidney transplant results in increased cost and complexity of management. For clinical care or a DGF trial, it would be ideal to accurately predict individual DGF risk and provide preemptive treatment. A calculator developed by Irish et al has been useful for predicting population but not individual risk. METHODS: We analyzed the Irish calculator (IC) in the DeKAF prospective cohort (incidence of DGF = 20.4%) and investigated potential improvements. RESULTS: We found that the predictive performance of the calculator in those meeting Irish inclusion criteria was comparable with that reported by Irish et al. For cohorts excluded by Irish: (a) in pump-perfused kidneys, the IC overestimated DGF risk; (b) in simultaneous pancreas kidney transplants, the DGF risk was exceptionally low. For all 3 cohorts, there was considerable overlap in IC scores between those with and those without DGF. Using a modified definition of DGF-excluding those with single dialysis in the first 24 h posttransplant-we found that the calculator had similar performance as with the traditional DGF definition. Studying whether DGF prediction could be improved, we found that recipient cardiovascular disease was strongly associated with DGF even after accounting for IC-predicted risk. CONCLUSIONS: The IC can be a useful population guide for predicting DGF in the population for which it was intended but has limited scope in expanded populations (SPK, pump) and for individual risk prediction. DGF risk prediction can be improved by inclusion of recipient cardiovascular disease.
Authors: Peter Schnuelle; Uwe Gottmann; Hannes Köppel; Paul Thomas Brinkkoetter; Stefan Krzossok; Johannes Weiss; Wilhelm Schmitt; Benito A Yard; Matthias Heinrich Martin Schwarzbach; Stefan Post; Fokko Johannes van der Woude; Rainer Birck Journal: Nephrol Dial Transplant Date: 2006-09-25 Impact factor: 5.992
Authors: M Cavaillé-Coll; S Bala; E Velidedeoglu; A Hernandez; P Archdeacon; G Gonzalez; C Neuland; J Meyer; R Albrecht Journal: Am J Transplant Date: 2013-04-08 Impact factor: 8.086