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Determinants of kidney transplant candidates' decision to accept organ donor intervention transplants and participate in post-transplant research: A conjoint analysis.

Elisa J GordonPeter L AbtJungwha LeeElizabeth KnopfCaitlin PhillipsFrancisca BermudezLakshman KrishnamurthiHuseyin S KaracaRobert VeatchRichard KnightPaul T ConwaySue DunnPeter P Reese
Published in: Clinical transplantation (2021)
Deceased organ donor intervention research aims to increase organ quality and quantity for transplantation. We assessed the proportion of kidney transplant candidates who would accept "intervention organs," participate in organ intervention research, and factors influencing acceptance. Kidney transplant candidates were presented 12 hypothetical scenarios, which varied three attributes, donor age, predicted waiting time to receive another organ offer, and research risk to the organ. Candidates were also randomly assigned to one of two conditions varying recipient risk. For each scenario, candidates agreed to accept the intervention organ or remain waitlisted. We fit a multivariable logit model to determine the association between scenario attributes and the acceptance decision. Of 249 participants, most (96%) accepted intervention organs under some or all conditions. Factors independently associated with candidates' greater likelihood of accepting an intervention organ included: low risk to the kidney from the intervention (OR 20.53 [95% Confidence Interval (CI), 13.91-30.29]); younger donor age (OR 3.72 [95% CI, 2.83-4.89]), longer time until the next organ offer (OR 3.48 [95% CI, 2.65-4.57]), and greater trust in their transplant physician (OR 1.03 [95% CI, 1.00-1.06]). Candidates with a lower likelihood of acceptance had been waitlisted longer (OR 0.97 per month [95% CI, 0.96-0.99]) and were Black (OR 0.21 [95% CI, 0.08-0.55]). Most candidates would accept an intervention organ, which should encourage transplant leaders to conduct deceased donor organ intervention trials.
Keyphrases
  • randomized controlled trial
  • primary care
  • healthcare
  • mesenchymal stem cells
  • social media
  • health information
  • data analysis