Transfusion‐related acute lung injury risk mitigation: an update
Bibliographic record
Abstract
Transfusion-related acute lung injury (TRALI) is a life-threatening complication of transfusion. Greater understanding of the pathophysiology of this syndrome has much improved during the last two decades. Plasma-containing components from female donors with leucocyte antibodies were responsible for the majority of TRALI fatalities before mitigation strategies were implemented. Over the past 15 years, measures to mitigate risk for TRALI have been implemented worldwide and they continued to evolve with time. The AABB requires that all plasma containing components and whole blood for transfusion must be collected from men, women who have not been pregnant, or women who have tested negative for human leucocyte antigen antibodies. Although the incidence of TRALI has decreased following the institution of TRALI mitigation strategies, TRALI is still the most common cause of transfusion-associated death in the United States. In this review, we focus on TRALI risk mitigation strategies. We describe the measures taken by blood collection facilities to reduce the risk of TRALI in the United States, Canada and European countries. We also review the literature for the effectiveness of these measures.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| 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) | 0.005 | 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".