Your browser doesn't support javascript.
loading
Probabilistic mathematical modelling to predict the red cell phenotyped donor panel size.
Best, Denisse; Burrage, Kevin; Burrage, Pamela; Donovan, Diane; Ginige, Shamila; Powley, Tanya; Thompson, Bevan; Daly, James.
Afiliación
  • Best D; Australian Red Cross Lifeblood, Brisbane, Queensland, Australia.
  • Burrage K; School of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia.
  • Burrage P; School of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia.
  • Donovan D; School of Mathematics and Physics, University of Queensland, Brisbane, Queensland, Australia.
  • Ginige S; Australian Red Cross Lifeblood, Brisbane, Queensland, Australia.
  • Powley T; Australian Red Cross Lifeblood, Brisbane, Queensland, Australia.
  • Thompson B; School of Mathematics and Physics, University of Queensland, Brisbane, Queensland, Australia.
  • Daly J; Australian Red Cross Lifeblood, Brisbane, Queensland, Australia.
PLoS One ; 17(11): e0276780, 2022.
Article en En | MEDLINE | ID: mdl-36367895
ABSTRACT
In the last decade, Australia has experienced an overall decline in red cell demand, but there has been an increased need for phenotyped matched red cells. Lifeblood and mathematicians from Queensland universities have developed a probabilistic model to determine the percentage of the donor panel that would need extended antigen typing to meet this increasing demand, and an estimated timeline to achieve the optimum required phenotyped (genotyped) panel. Mathematical modelling, based on Multinomial distributions, was used to provide guidance on the percentage of typed donor panel needed, based on recent historical blood request data and the current donor panel size. Only antigen combinations determined to be uncommon, but not rare, were considered. Simulations were run to attain at least 95% success percentage. Modelling predicted a target of 38% of the donor panel, or 205,000 donors, would need to be genotyped to meet the current demand. If 5% of weekly returning donors were genotyped, this target would be reached within 12 years. For phenotyping, 35% or 188,000 donors would need to be phenotyped to meet Lifeblood's demand. With the current level of testing, this would take eight years but could be performed within three years if testing was increased to 9% of weekly returning donors. An additional 26,140 returning donors need to be phenotyped annually to maintain this panel. This mathematical model will inform business decisions and assist Lifeblood in determining the level of investment required to meet the desired timeline to achieve the optimum donor panel size.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Donantes de Sangre / Eritrocitos Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2022 Tipo del documento: Article País de afiliación: Australia

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Donantes de Sangre / Eritrocitos Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2022 Tipo del documento: Article País de afiliación: Australia