Transfusion-related acute lung injury: epidemiology and a prospective analysis of etiologic factors
Bibliographic record
Abstract
Transfusion-related acute lung injury (TRALI) is a life-threatening complication of hemotherapy. We report a series of 90 TRALI reactions in 81 patients secondary to transfusion with whole blood platelets (72 reactions), apheresis platelets (2), packed red cells (15), and plasma (1). The overall prevalence was 1 in 1120 cellular components. To examine the epidemiology of TRALI, we completed a nested case-control study of the first 46 patients with TRALI compared with 225 controls who had received transfusions. We then completed a prospective analysis of possible biologic response modifiers responsible for 51 of the TRALI cases, including human leukocyte antigen (HLA) class I, class II, and granulocyte antibodies in donors and neutrophil (PMN) priming activity in the plasma of the implicated units and recipients. Two groups were at risk: patients with hematologic malignancies (P <.0004) and patients with cardiac disease (P <.0006). TRALI was associated with older platelets (P =.014). In the prospective study, antileukocyte antibodies were found in only 3.6% of cases. The implicated blood components had greater PMN priming activity than controls (P <.05), and compared with pretransfusion samples, TRALI patients' plasma demonstrated increases in both interleukin 6 (IL-6) and lipid (neutral lipids and lysophosphatidylcholines) priming activity (P <.05). We conclude that TRALI may be more frequent than previously recognized and that patient susceptibility, product age, and increased levels of bioactive lipids in components may predispose patients to TRALI. TRALI, like the acute respiratory distress syndrome, may be a 2-event phenomenon with both recipient predisposition and factors in the stored units playing major roles.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| 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 | 0.000 | 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".