A new method of modelling early plasma creatinine changes predicts 1-year graft function after kidney transplantation

Scand J Clin Lab Invest. 2016 Jul;76(4):319-23. doi: 10.3109/00365513.2016.1161233. Epub 2016 Apr 11.

Abstract

Background: Delayed graft function after renal transplantation is associated with inferior long-term outcome. To evaluate the impact of slow onset graft function, we aimed to model and correlate early changes in plasma creatinine (p-cr) with long-term graft function.

Materials: In a single centre observational study of 100 kidney transplants we identified all p-cr measurements from the time of transplantation until 30 days post-transplant or last post-transplant dialysis, and correlated this with estimated glomerular filtration rate (eGFR) 1 year after transplantation. The initial changes in p-cr were modelled for each patient using an exponential, logistic, or linear model, and the time to a 50% decrease in p-cr (tCr50) was estimated.

Results: Linear regression analysis showed a negative correlation between tCr50 and eGFR 1 year post-transplant (n = 96, r = -0.369, β = -0.112, p = 0.0002). The correlation was maintained when corrected for the relevant recipient and donor characteristics. tCr50 correlated positively with the number of hospitalisation days, the number of graft ultrasound examinations, and the number of biopsies.

Conclusions: A modelled time to a 50% decrease in p-cr predicts 1-year graft function. tCr50 may be a relevant surrogate endpoint in renal transplant studies aimed at improving long-term function by reducing the incidence of slow onset graft function.

Keywords: Renal; creatinine; delayed graft function; glomerular filtration rate; transplantation.

Publication types

  • Clinical Trial

MeSH terms

  • Biomarkers / analysis
  • Biomarkers / blood
  • Creatinine / analysis
  • Creatinine / blood*
  • Decision Support Techniques*
  • Glomerular Filtration Rate
  • Graft Rejection / metabolism*
  • Humans
  • Kidney / surgery
  • Kidney Function Tests
  • Kidney Transplantation
  • Linear Models
  • Male
  • Middle Aged
  • Models, Statistical*

Substances

  • Biomarkers
  • Creatinine