Literature DB >> 16534482

Increasing the opportunity of live kidney donation by matching for two- and three-way exchanges.

Susan L Saidman1, Alvin E Roth, Tayfun Sönmez, M Utku Unver, Francis L Delmonico.   

Abstract

BACKGROUND: To expand the opportunity for paired live donor kidney transplantation, computerized matching algorithms have been designed to identify maximal sets of compatible donor/recipient pairs from a registry of incompatible pairs submitted as candidates for transplantation.
METHODS: Demographic data of patients who had been evaluated for live donor kidney transplantation but found to be incompatible with their potential donor (because of ABO blood group or positive crossmatch) were submitted for computer analysis and matching. Data included ABO and HLA types of donor and recipient, %PRA and specificity of recipient alloantibody, donor/recipient relationship, and the reason the donor was incompatible. The data set used for the initial simulation included 29 patients with one donor each and 16 patients with multiple donors for a total of 45 patients and 68 donor/patient pairs. In addition, a simulation based on OPTN/SRTR data was used to further assess the practical importance of multiple exchange combinations.
RESULTS: If only exchanges involving two patient-donor pairs were allowed, a maximum of 8 patient-donor pairs in the data set could exchange kidneys. If three-way exchanges were also allowed, a maximum of 11 pairs could exchange kidneys. Simulations with OPTN/SRTR data demonstrate that the increase in the number of potential transplants if three-way exchanges are allowed is robust, and does not depend on the particular patients in our sample.
CONCLUSIONS: A computerized matching protocol can be used to identify donor/recipient pairs from a registry of incompatible pairs who can potentially enter into donor exchanges that otherwise would not readily occur.

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Mesh:

Year:  2006        PMID: 16534482     DOI: 10.1097/01.tp.0000195775.77081.25

Source DB:  PubMed          Journal:  Transplantation        ISSN: 0041-1337            Impact factor:   4.939


  11 in total

1.  Concerns of ABO incompatible and crossmatch-positive potential donors and recipients about participating in kidney exchanges.

Authors:  James R Rodrigue; Ruthanne Leishman; Tanya Vishnevsky; Amy Evenson; Didier A Mandelbrot
Journal:  Clin Transplant       Date:  2015-02-03       Impact factor: 2.863

Review 2.  The Benefits of a Local Kidney Exchange.

Authors:  Mohamed Saleh Ismail; Matthew Cusick; Nhu Thao Nguyen Galvan
Journal:  Tex Heart Inst J       Date:  2019-02-01

3.  Evaluation of kidney transplantation programmes using system simulation.

Authors:  S Prasanna Devi; S Saravana Kumar; K Suryaprakasa Rao
Journal:  J Med Syst       Date:  2010-09-01       Impact factor: 4.460

4.  Virtual Crossmatching in Kidney Transplantation, Shiraz Experience in Development of a Web-Based Program.

Authors:  N Jamshidian Tehrani; B Geramizadeh; S A Malekhosseini; S Nikeghbalian; A Bahador; S Gholami; G A Raees Jalali; J Roozbeh; M H Anbardar; N Soleimani; N Rasaei; S Mohammadzadeh
Journal:  Int J Organ Transplant Med       Date:  2021

5.  A Systematic Review of Kidney Transplantation Decision Modelling Studies.

Authors:  Mohsen Yaghoubi; Sonya Cressman; Louisa Edwards; Steven Shechter; Mary M Doyle-Waters; Paul Keown; Ruth Sapir-Pichhadze; Stirling Bryan
Journal:  Appl Health Econ Health Policy       Date:  2022-08-09       Impact factor: 3.686

6.  Living donor kidney paired exchange: An observational study.

Authors:  Pukar Chandra Shrestha; Tika Ram Bhandari; Rojan Adhikari; Hari Baral; Rakesh Kumar Verma; Kalpana Kumari Shrestha
Journal:  Ann Med Surg (Lond)       Date:  2022-05-14

7.  The decline in living kidney donation in the United States: random variation or cause for concern?

Authors:  James R Rodrigue; Jesse D Schold; Didier A Mandelbrot
Journal:  Transplantation       Date:  2013-11-15       Impact factor: 4.939

Review 8.  Past, present and future of kidney paired donation transplantation in India.

Authors:  Vivek B Kute; Himanshu V Patel; Pankaj R Shah; Pranjal R Modi; Veena R Shah; Sayyed J Rizvi; Bipin C Pal; Manisha P Modi; Priya S Shah; Umesh T Varyani; Pavan S Wakhare; Saiprasad G Shinde; Vijay A Ghodela; Minaxi H Patel; Varsha B Trivedi; Hargovind L Trivedi
Journal:  World J Transplant       Date:  2017-04-24

9.  Ant Lion Optimization algorithm for kidney exchanges.

Authors:  Eslam Hamouda; Sara El-Metwally; Mayada Tarek
Journal:  PLoS One       Date:  2018-05-03       Impact factor: 3.752

10.  Accounting for Fairness in a Two-Stage Stochastic Programming Model for Kidney Exchange Programs.

Authors:  Hyunwoo Lee; Seokhyun Chung; Taesu Cheong; Sang Hwa Song
Journal:  Int J Environ Res Public Health       Date:  2018-07-14       Impact factor: 4.614

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