<scp>ABO</scp>‐mismatched platelet and plasma transfusion practices and the potential for transfusion‐related alpha‐gal syndrome: The Biomedical Excellence for Safer Transfusion Collaborative Study
Bibliographic record
Abstract
BACKGROUND: Alpha-gal syndrome (AGS) is caused by IgE antibodies against the alpha-gal oligosaccharide, which is structurally similar to the Group B antigen. Recent case reports of severe allergic transfusion reactions (ATRs) in Group O patients receiving Group B plasma and platelets raise the possibility of a new adverse event, herein called transfusion-related AGS (TRAGS). The primary goal of this study was to assess the frequency of Groups B and AB plasma and platelet transfusions to Group O patients. STUDY DESIGN AND METHODS: In this multi-site retrospective study, participating sites submitted the numbers of platelet and plasma transfusions administered during a 2-year period categorized by patient and product ABO group. RESULTS: Fourteen sites from 10 countries participated. Group O patients received Group AB for an average of 9.9% (range 2.8%-29.2%) of plasma transfusions and Group B for 3.2% (0%-12.8%). AB plasma transfusion to Group O patients represented 4.5% (0.9%-14.6%) of the total plasma transfused; Group B 1.4% (0%-5.1%). Group O patients received Group AB for an average of 1.5% (range 0%-5.9%) of platelet transfusions and Group B for 4.1% (0%-14.2%). AB platelet transfusion to Group O patients represented 0.6% (0%-2.7%) of the total platelets transfused; Group B platelets were 1.8% (0%-6.7%). DISCUSSION: Evidence supporting the possibility of a new adverse event, TRAGS, is accumulating. This study quantifies how often Group O patients may be exposed to Group B antigen in Group B or AB plasma and/or platelet transfusions, providing an estimate of the scope of potential risk for TRAGS.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".