The impact of donor ferritin testing on blood availability in Canada
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Iron depletion is a side effect of blood donation. Agencies have developed policies to test donors and to extend inter-donation intervals (IDIs) for individuals with low ferritin levels. Ferritin testing, however, has an impact on product availability due to longer IDIs and the effect of test results on donor behaviour. In this paper we apply a model to evaluate the impact of ferritin testing in the Canadian donor population on whole blood donations. MATERIALS AND METHODS: A discrete event simulation was adopted for the study. The model represents a population of individuals that donate blood, are tested for ferritin levels, and may exit the system. Data for the simulation was derived from operational data, donor research studies from Canadian Blood Services and previously published sources. RESULTS: Red cell collections will decline by at least 3.1% and could decline by as much as 19.2% after ferritin testing is put in place. Requirements for new donors could rise by as much as 36.0%. CONCLUSION: The impact of ferritin testing on repeat donor behaviour, rather than extensions to the mandated inter-donation interval, is the largest factor influencing declines in whole blood donations. Because behaviour changes following the receipt of a low ferritin result, blood agencies must ensure that donors with low ferritin are motivated to modify their lifestyle and, when healthy, return to the donor pool.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".