Differences in the product characteristics and clinical use of granulocytes for transfusion: The <scp>BEST</scp> Collaborative study
Bibliographic record
Abstract
Abstract Background Whether granulocytes for transfusion are beneficial remains uncertain, although some evidence suggests that efficacy may be dose‐related. Granulocytes are mostly produced by apheresis procedure, but other means of production are increasingly used. Methods Centers that produce and/or use granulocytes were recruited through the BEST Collaborative and completed a detailed survey of granulocyte manufacture, specifications, clinical use, operational considerations, and data collection initiatives. Results Fifteen national, regional, and local producers and/or users of granulocytes were included. Granulocytes were produced from apheresis procedure ( n = 10), pooled buffy coats ( n = 2), single buffy coats ( n = 4) or pooling of residual leukocyte units from whole blood processing ( n = 1). The mean adult dose of granulocytes reported was 1.6 to 3.7 × 10 10 for apheresis, and 1.8 to 2.2 × 10 10 for pooled buffy coat granulocytes. For apheresis procedure donations, donor stimulation included steroids and/or granulocyte colony‐stimulating factor. Centers providing whole blood‐derived granulocytes reported shorter times from request to delivery than those using apheresis procedure products. Indications and product selection criteria were similar. The most frequently reported challenges with granulocytes were donor availability for apheresis procedure ( n = 7), short shelf life ( n = 5) and lack of evidence of efficacy ( n = 5). The cost of one unit of apheresis procedure granulocytes ranged from 568 to 7500 PPP‐USD, and for one pooled buffy coat unit was from 2208 to 2822 PPP‐USD. Conclusions We have highlighted differences in granulocyte production that are relevant for the design and interpretation of much needed international clinical studies.
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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 | 0.014 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".