Practices associated with ABO‐incompatible platelet transfusions: a BEST Collaborative international survey
Bibliographic record
Abstract
BACKGROUND: There is a lack of evidence for guiding the best strategy for ABO selection of platelet (PLT) transfusions. As a baseline for future studies, the BEST Collaborative performed an international survey of current practices in this area. STUDY DESIGN AND METHODS: An international survey was sent via BEST members to transfusion services and hospitals requesting the demographics of the transfused patient population, ABO matching policies, anti-A and anti-B measurements in PLT concentrates (PCs), and practices regarding ABO-incompatible PC transfusions to adult and pediatric patients. RESULTS: We received 126 responses from 14 countries, 59% from Europe. Most of them were from local/community (42%) and university hospitals (39%) serving between 500 and 1500 beds; 50.4% transfused fewer than 1000 PCs per year. One-fifth of respondents (19.4%, mainly local/community hospitals) did not have a written policy for selecting ABO-incompatible PCs. Significant practice variation was reported when ABO-mismatched PLTs were given to adults: for PCs suspended in 100% plasma, 29% to 43% of respondents selected any ABO group available; 52% to 61% selected units with compatible supernatant; and, in the case of minor ABO incompatibility, 43% to 54% did not take any specific action. In contrast if ABO-identical PCs were not available for a pediatric recipient, for PCs resuspended in 100% plasma, 71% to 82% selected PCs so the supernatant plasma would be compatible with patient's red blood cells. CONCLUSION: Considerable practice variation exists when transfusing ABO-incompatible PCs, suggesting an opportunity for research to inform evidence-based practices.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".