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CODUSA - Customize Optimal Donor Using Simulated Annealing In Heart Transplantation.

Ansari, Daniel LU ; Andersson, Bodil LU ; Ohlsson, Mattias LU ; Höglund, Peter LU ; Andersson, Roland LU and Nilsson, Johan LU (2013) In Scientific Reports 3(May,30).
Abstract
In heart transplantation, selection of an optimal recipient-donor match has been constrained by the lack of individualized prediction models. Here we developed a customized donor-matching model (CODUSA) for patients requiring heart transplantations, by combining simulated annealing and artificial neural networks. Using this approach, by analyzing 59,698 adult heart transplant patients, we found that donor age matching was the variable most strongly associated with long-term survival. Female hearts were given to 21% of the women and 0% of the men, and recipients with blood group B received identical matched blood group in only 18% of best-case match compared with 73% for the original match. By optimizing the donor profile, the survival... (More)
In heart transplantation, selection of an optimal recipient-donor match has been constrained by the lack of individualized prediction models. Here we developed a customized donor-matching model (CODUSA) for patients requiring heart transplantations, by combining simulated annealing and artificial neural networks. Using this approach, by analyzing 59,698 adult heart transplant patients, we found that donor age matching was the variable most strongly associated with long-term survival. Female hearts were given to 21% of the women and 0% of the men, and recipients with blood group B received identical matched blood group in only 18% of best-case match compared with 73% for the original match. By optimizing the donor profile, the survival could be improved with 33 months. These findings strongly suggest that the CODUSA model can improve the ability to select optimal match and avoid worst-case match in the clinical setting. This is an important step towards personalized medicine. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Scientific Reports
volume
3
issue
May,30
publisher
Nature Publishing Group
external identifiers
  • wos:000319653300003
  • pmid:23722478
  • scopus:84902939644
ISSN
2045-2322
DOI
10.1038/srep01922
language
English
LU publication?
yes
id
12d99e93-e726-42f7-9951-3a61dd8d170a (old id 3913860)
alternative location
http://www.ncbi.nlm.nih.gov/pubmed/23722478?dopt=Abstract
date added to LUP
2013-07-01 10:32:34
date last changed
2019-01-06 09:31:53
@article{12d99e93-e726-42f7-9951-3a61dd8d170a,
  abstract     = {In heart transplantation, selection of an optimal recipient-donor match has been constrained by the lack of individualized prediction models. Here we developed a customized donor-matching model (CODUSA) for patients requiring heart transplantations, by combining simulated annealing and artificial neural networks. Using this approach, by analyzing 59,698 adult heart transplant patients, we found that donor age matching was the variable most strongly associated with long-term survival. Female hearts were given to 21% of the women and 0% of the men, and recipients with blood group B received identical matched blood group in only 18% of best-case match compared with 73% for the original match. By optimizing the donor profile, the survival could be improved with 33 months. These findings strongly suggest that the CODUSA model can improve the ability to select optimal match and avoid worst-case match in the clinical setting. This is an important step towards personalized medicine.},
  articleno    = {1922},
  author       = {Ansari, Daniel and Andersson, Bodil and Ohlsson, Mattias and Höglund, Peter and Andersson, Roland and Nilsson, Johan},
  issn         = {2045-2322},
  language     = {eng},
  number       = {May,30},
  publisher    = {Nature Publishing Group},
  series       = {Scientific Reports},
  title        = {CODUSA - Customize Optimal Donor Using Simulated Annealing In Heart Transplantation.},
  url          = {http://dx.doi.org/10.1038/srep01922},
  volume       = {3},
  year         = {2013},
}