Variations in hemoglobin measurement and eligibility criteria across blood donation services are associated with differing low‐hemoglobin deferral rates: a BEST Collaborative study
Bibliographic record
Abstract
BACKGROUND: Determination of blood donor hemoglobin (Hb) levels is a pre-requisite to ensure donor safety and blood product quality. We aimed to identify Hb measurement practices across blood donation services and to what extent differences associate with low-Hb deferral rates. METHODS: An online survey was performed among Biomedical Excellence for Safer Transfusion (BEST) Collaborative members, extended with published data. Multivariable negative-binomial regression models were built to estimate adjusted associations of minimum donation intervals, Hb cut-offs (high, ≥13.5 g/dL in men or ≥ 12.5 g/dL in women, vs. lower values), iron monitoring (yes/no), providing or prescribing iron supplementation (yes/no), post-versus pre-donation Hb measurement and geographical location (Asian vs. rest), with low-Hb deferral rates. RESULTS: Data were included from 38 blood services. Low-Hb deferral rates varied from 0.11% to 8.81% among men and 0.84% to 31.85% among women. Services with longer minimum donation intervals had significantly lower deferral rates among both women (rate ratio, RR 0.53, 95%CI 0.33-0.84) and men (RR 0.53, 95%CI 0.31-0.90). In women, iron supplementation was associated with lower Hb deferral rates (RR 0.47, 95%CI 0.23-0.94). Finally, being located in Asia was associated with higher low-Hb deferral rates; RR 9.10 (95%CI 3.89-21.27) for women and 6.76 (95%CI 2.45-18.68) for men. CONCLUSION: Differences in Hb measurement and eligibility criteria, particularly longer donation intervals and iron supplementation in women, are associated with variations in low-Hb deferral rates. These insights could help improve both blood donation service efficiency and donor care.
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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 | 0.001 | 0.000 |
| 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 | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".