Conversion to the buffy coat method and quality of frozen plasma derived from whole blood donations in Canada
Bibliographic record
Abstract
BACKGROUND: Canada converted from the platelet-rich plasma (PRP) method to the buffy coat (BC) method of processing whole blood donations between 2006 and 2008. We measured coagulation variables in plasma units during this transition, in 2006 (PRP only), 2007 (BC and PRP), and 2008 (BC only) to test the hypothesis that this conversion would not affect frozen plasma (FP) quality. STUDY DESIGN AND METHODS: Fresh-frozen plasma (FFP; frozen within 8 hr of collection) or FP (frozen within 24 hr of collection) units were shipped on dry ice from 12 plasma manufacturing sites, thawed, and characterized using an automated coagulation analyzer, at a single testing site. RESULTS: FP made by the BC method (FP-BC) exhibited fibrinogen, Factor (F)V, ABO-matched FVIII, and antithrombin levels at least as high as FP made by the PRP method (FP-PRP) and supported global clotting, as measured by prothrombin time or activated partial thromboplastin time, to an indistinguishable extent as FP-PRP. FP-BC and FP-PRP did not differ in ABO-matched FVIII levels, but both contained 30% to 35% less FVIII than FFP. There was no discernible effect of the site of manufacturing on plasma quality. FP-BC units leukoreduced by centrifugation contained more FV activity than those leukoreduced by filtration, but the difference was unlikely to be of clinical significance. CONCLUSION: Our data suggest that no reduction in FP quality, at least in the characteristics we tested, accompanied the switch from the PRP to the BC method processing of whole blood donations in Canada.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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 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".