4.2 Article

Prediction and impact of personalized donation intervals

期刊

VOX SANGUINIS
卷 117, 期 4, 页码 504-512

出版社

WILEY
DOI: 10.1111/vox.13223

关键词

blood collection; donor health; haemoglobin measurement

资金

  1. European Blood Alliance research grant [2019-02]
  2. Finnish Red Cross Blood Service (FRCBS)

向作者/读者索取更多资源

The study evaluated the possibility of predicting blood donor deferral due to low hemoglobin levels using computational prediction tools. While linear predictors were found to generally predict hemoglobin levels well, difficulties were encountered in predicting low hemoglobin values. The use of any of the predictors in blood collection could potentially lead to cost savings and benefits for blood donors and establishments.
Background and Objectives Deferral of blood donors due to low haemoglobin (Hb) is demotivating to donors, can be a sign for developing anaemia and incurs costs for blood establishments. The prediction of Hb deferral has been shown to be feasible in a number of studies based on demographic, Hb measurement and donation history data. The aim of this paper is to evaluate how state-of-the-art computational prediction tools can facilitate nationwide personalized donation intervals. Materials and Methods Using donation history data from the last 20 years in Finland, FinDonor blood donor cohort data and blood service Biobank genotyping data, we built linear and non-linear predictors of Hb deferral. Based on financial data from the Finnish Red Cross Blood Service, we then estimated the economic impacts of deploying such predictors. Results We discovered that while linear predictors generally predict Hb relatively well, they have difficulties in predicting low Hb values. Overall, we found that non-linear or linear predictors with or without genetic data performed only slightly better than a simple cutoff based on previous Hb. However, if any of our deferral prediction methods are used to assign temporary prolongations of donation intervals for females, then our calculations indicate cost savings while maintaining the blood supply. Conclusion We find that even though the prediction accuracy is not very high, the actual use of any of our predictors in blood collection is still likely to bring benefits to blood donors and blood establishments alike.

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