[Less iron deficiency in whole-blood donors: the effect of ferritin-guided donation intervals].

Objective: To evaluate the effect of ferritin-guided donation intervals on haemoglobin (Hb) and ferritin levels, iron deficiency and low Hb deferrals in whole-blood donors.

Design: A cluster-randomized stepped-wedge trial.

Methods: In 2017-2019, Sanquin gradually implemented ferritin-guided donation intervals.

Effectiveness of ferritin-guided donation intervals in whole-blood donors in the Netherlands (FIND'EM): a stepped-wedge cluster-randomised trial.

Background: Whole-blood donors are at increased risk for iron deficiency and anaemia. The current standard of haemoglobin monitoring is insufficient to ensure the maintenance of proper iron reserves and donor health. We aimed to determine the effects of ferritin-guided donation intervals for blood donor health and blood supply in the Netherlands.

Predicting haemoglobin deferral using machine learning models: Can we use the same prediction model across countries?

Background And Objectives: Personalized donation strategies based on haemoglobin (Hb) prediction models may reduce Hb deferrals and hence costs of donation, meanwhile improving commitment of donors. We previously found that prediction models perform better in validation data with a high Hb deferral rate. We therefore investigate how Hb deferral prediction models perform when exchanged with other blood establishments.

An international comparison of haemoglobin deferral prediction models for blood banking.

Background And Objectives: Blood banks use a haemoglobin (Hb) threshold before blood donation to minimize donors' risk of anaemia. Hb prediction models may guide decisions on which donors to invite, and should ideally also be generally applicable, thus in different countries and settings. In this paper, we compare the outcome of various prediction models in different settings and highlight differences and similarities.