Identifying risk factors in renal allografts before transplant: Machine-measured renal resistance and posttransplant allograft survival

Yuriy Y. Yushkov, Jeffrey Stern, Alexis Ying, Nikolina Icitovic, Steven H. Dikman, Maunil Sheth, Michael J. Goldstein

Research output: Contribution to journalArticle

10 Scopus citations

Abstract

Enhancement of renal allograft function and survival in an era where expanded criteria donors are increasingly used requires validated selection criteria. The goal of this retrospective study was to evaluate the significance of pretransplant donor and allograft parameters to identify risk factors that can be used in a model to predict 1-year allograft outcomes. Donor demographic factors, donor type, and allograft parameters such as biopsy results and machine-measured renal resistance were correlated with 1-year graft outcome. The Kaplan-Meier method was used to estimate graft survival using the categorical predictors of donor type, donor age, and machinemeasured renal resistance at 1.5, 3, and 5 hours. The log-rank test was used to test the difference in survival curves between cohorts. The Cox regression analysis was used to estimate hazard ratios for machine-measured renal resistance, donor age, donor terminal creatinine level, donor's estimated glomerular filtration rate, cold ischemia time, and percent glomerulosclerosis. The data show that machine-measured renal resistance at 3 and 5 hours has a statistically significant inverse relationship to 1-year graft survival. All other risk factors had no correlation with 1-year graft survival. The machine-measured renal resistance at 3 hours is the earliest significant predictor of 1-year allograft outcome.

Original languageEnglish (US)
Pages (from-to)175-182
Number of pages8
JournalProgress in Transplantation
Volume22
Issue number2
DOIs
StatePublished - Jun 1 2012

ASJC Scopus subject areas

  • Transplantation

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