Adapting to supply‐and‐demand emerging trends for antigen‐negative red blood cell units
Bibliographic record
Abstract
BACKGROUND: A global downtrend in blood usage has been observed by many countries, while the demand for antigen-negative red blood cell (RBC) units used in antigen-matched transfusions keeps increasing. The declining number of units collected exposes blood providers to a rapidly evolving supply challenge. METHODS: This study was conducted retrospectively with use of internal data analysis to weigh Québec's situation regarding global and antigen-negative RBC demand, to measure the effects of community-directed recruitment and blood drives, and to evaluate the benefits of mass-scale RBC genotyping. RESULTS: Our findings confirm a global RBC usage downtrend of over 20% total in the past 10 years with a steady antigen-negative usage and highlight the most requested negative antigen combinations. Our data also show our +39.5% progress regarding the number of Black donors recruited for antigen matching of patients with sickle cell disease in the past 3 years, as well as a constantly growing number of just-in-time blood collection for complex orders. Finally, our data summarize the efficiency of our mass-scale RBC genotyping efforts. CONCLUSION: Altogether, this study confirms the demand trends for regular and antigen-negative RBC units in Québec and the efficient effects of our recruitment and typing strategies.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| 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".