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Updated: May 10, 2026

Robot-Assisted Kidney Transplantation
Published on: July 19, 2021
A new kidney allocation policy in Chile: computer-based simulations
J Domínguez1, R Harrison, R Atal
1Facultad de Medicina, Departamento de Urología, Pontificia Universidad Católica de Chile, Santiago, Chile. javierdomi@hotmail.com
Introduction:
Kidney allocation should reach a balance between equity and efficiency. In Chile kidneys are allocated based on ABO matching, first to medical priorities and then according to a point scheme considering human leukocyte antigen (HLA) match (60%), waiting list time (20%), and panel-reactive antibodies (PRA; 20%); pediatric recipients receive extra points. A new policy maintains ABO matching and medical priorities as the first step, but incorporates other successive steps: previous living donors donors, 0 mismatch, pediatric recipients, and finally all other recipients according to a point scheme incorporating recipient age, HLA match, PRA, and time on waiting list with similar proportions. We compared the resulting transplantations using the new versus the older allocation policy.
Methods:
We analyzed computer-generated simulations using actual patients (N = 1176) on the Chilean waiting list in 2011 with the 300 donors over the previous 3 years.
Results:
The new policy a significantly decreased recipient age from 43 ± 0.3 years to 41 ± 0.3 and increased the number of 0-mismatched transplantations from 3% to 4%. The mean HLA mismatch increased from 2.8 ± 0.1 to 3.6 ± 0.1. Waiting time increased from a mean of 38 ± 1 months to 40 ± 1 months, but patients remaining on the waiting list had less waiting time with the new rule.
Conclusions:
With the proposed changes younger patients are being privileged and the importance of compatibility is diminished (except for 0-mismatched transplantations). The chance of a good match is directly related to the size of the recipient pool, thus an allocation policy that privileges HLA matching in a restricted recipient pool is especially unfavorable for younger patients. Including age of the recipient as a continuum can help to compensate for this lack of equity. Computer-generated simulations can help discern which policies are best suited for each country based on their local characteristics.
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