Metabolic effects of kidney donation: A Bayesian analysis of matched cohorts.

Abstract

The kidney is a notable site of glycolysis, gluconeogenesis, and fatty acid oxidation. Loss of a kidney after kidney donation might, therefore, affect the glucose and lipid metabolism of the donors. This matched cohort study investigated the effect of nephrectomy on glucose and lipid metabolisms using Bayesian hypothesis testing. There were 77 pairs of matched donor-control pairs in the present study. Clinical and laboratory data of the participants, at baseline and 1-year, were extracted from electronic medical records. Comparisons between donor and control groups were performed using the Bayesian independent samples t-test or Bayesian Mann-Whitney test. The Bayes Factor for alternative hypothesis over null hypothesis (BF10 ) was used to compare the two competing hypotheses. The BF10 of 3 or more was considered evidence for the alternative hypothesis. Comparing changes from baseline to 1-year between donors and controls, the BF10 of triglycerides, high-density lipoprotein cholesterol (HDL-C), triglyceride-glucose (TyG) index of insulin resistance, and estimated glomerular filtration rate (eGFR) were 7.95, 3.96, 30.13, and 1.32 x 1041 , respectively signifying that the change of these variables in the donors differed from those in the controls (alternative hypothesis). Triglyceride, HDL-C, and TyG index of the donors increased more than those of the controls while eGFR of the donor decreased more than that of the controls. Our data suggest that triglycerides and insulin resistance increase after donor nephrectomy. Kidney donors should be informed about these metabolic changes and should adhere to lifestyle recommendations that may mitigate insulin resistance.