Frequent blood donations alter susceptibility of red blood cells to storage‐ and stress‐induced hemolysis
Bibliographic record
Abstract
BACKGROUND: Frequent whole blood donations increase the prevalence of iron depletion in blood donors, which may subsequently interfere with normal erythropoiesis. The purpose of this study was to evaluate the associations between donation frequency and red blood cell (RBC) storage stability in a racially/ethnically diverse population of blood donors. STUDY DESIGN: Leukoreduced RBC concentrate-derived samples from 13,403 donors were stored for 39 to 42 days (1-6°C) and then evaluated for storage, osmotic, and oxidative hemolysis. Iron status was evaluated by plasma ferritin measurement and self-reported intake of iron supplements. Donation history in the prior 2 years was obtained for each subject. RESULTS: Frequent blood donors enrolled in this study were likely to be white, male, and of older age (56.1 ± 5.0 years). Prior donation intensity was negatively associated with oxidative hemolysis (p < 0.0001) in multivariate analyses correcting for age, sex, and race/ethnicity. Increased plasma ferritin concentration was associated with increased RBC susceptibility to each of the three measures of hemolysis (p < 0.0001 for all), whereas self-reported iron intake was associated with reduced susceptibility to osmotic and oxidative hemolysis (p < 0.0001 for both). CONCLUSIONS: Frequent blood donations may alter the quality of blood components by modulating RBC predisposition to hemolysis. RBCs collected from frequent donors with low ferritin have altered susceptibility to hemolysis. Thus, frequent donation and associated iron loss may alter the quality of stored RBC components collected from iron-deficient donors. Further investigation is necessary to assess posttransfusion safety and efficacy in patients receiving these RBC products.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".