Prediction of measured GFR after living kidney donation from pre-donation parameters

Marco Van Londen, Jessica Van Der Weijden, Robert S. Niznik, Aidan F. Mullan, Stephan J.L. Bakker, Stefan P. Berger, Ilja M. Nolte, Jan Stephan F. Sanders, Gerjan Navis, Andrew D. Rule, Martin H. De Borst

Research output: Contribution to journalArticlepeer-review

Abstract

Background: One of the challenges in living kidney donor screening is to estimate remaining kidney function after donation. Here we developed a new model to predict post-donation measured glomerular filtration rate (mGFR) from pre-donation serum creatinine, age and sex. Methods: In the prospective development cohort (TransplantLines, n = 511), several prediction models were constructed and tested for accuracy, precision and predictive capacity for short- and long-term post-donation 125I-iothalamate mGFR. The model with optimal performance was further tested in specific high-risk subgroups (pre-donation eGFR <90 mL/min/1.73 m2, a declining 5-year post-donation mGFR slope or age >65 years) and validated in internal (n = 509) and external (Mayo Clinic, n = 1087) cohorts. Results: In the development cohort, pre-donation estimated GFR (eGFR) was 86 ± 14 mL/min/1.73 m2 and post-donation mGFR was 64 ± 11 mL/min/1.73 m2. Donors with a pre-donation eGFR ≥90 mL/min/1.73 m2 (present in 43%) had a mean post-donation mGFR of 69 ± 10 mL/min/1.73 m2 and 5% of these donors reached an mGFR <55 mL/min/1.73 m2. A model using pre-donation serum creatinine, age and sex performed optimally, predicting mGFR with good accuracy (mean bias 2.56 mL/min/1.73 m2, R2 = 0.29, root mean square error = 11.61) and precision [bias interquartile range (IQR) 14 mL/min/1.73 m2] in the external validation cohort. This model also performed well in donors with pre-donation eGFR <90 mL/min/1.73 m2 [bias 0.35 mL/min/1.73 m2 (IQR 10)], in donors with a negative post-donation mGFR slope [bias 4.75 mL/min/1.73 m2 (IQR 13)] and in donors >65 years of age [bias 0.003 mL/min/1.73 m2 (IQR 9)]. Conclusions: We developed a novel post-donation mGFR prediction model based on pre-donation serum creatinine, age and sex.

Original languageEnglish (US)
Pages (from-to)212-221
Number of pages10
JournalNephrology Dialysis Transplantation
Volume38
Issue number1
DOIs
StatePublished - Jan 1 2023

Keywords

  • donor selection
  • glomerular filtration rate
  • kidney function
  • living kidney donation
  • renal function equations

ASJC Scopus subject areas

  • Nephrology
  • Transplantation

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