Transfusion‐related acute lung injury: reports to the French Hemovigilance Network 2007 through 2008
Bibliographic record
Abstract
BACKGROUND: Transfusion-related acute lung injury (TRALI) is a major cause of transfusion-related mortality and morbidity. Epidemiologic studies using data from national transfusion schemes can help achieve a better understanding of TRALI incidence. STUDY DESIGN AND METHODS: A multidisciplinary working group analyzed TRALI cases extracted from the French Hemovigilance Network Database (2007-2008). All notified cases were reviewed for diagnosis. Those meeting the Canadian Consensus Conference criteria for TRALI were classified according to imputability to transfusion and clinical severity. Patient data (clinical characteristics, number and types of products transfused, and serology results) were obtained. RESULTS: There were 62 TRALI cases and 23 possible TRALI cases during the 2-year period. An immune-mediated mechanism was identified in 30 of 50 TRALI cases with complete serology. TRALI was considered to be the cause of death in 7.1% of patients and might have contributed to death in an additional 9.4% of TRALI or possible TRALI patients. Occurrence ranked high in obstetrics (15%), after surgery (34%), and in hematologic malignancies (21%). Single-donor high-plasma-volume components were involved in half of the cases where the implicated blood product could be determined and carried the highest risk per component (1:31,000 for single-donor fresh-frozen plasma units and apheresis platelet [PLT] concentrates, and 1:173,000 for red blood cells). No incident could be definitively related to the transfusion of solvent/detergent-treated pooled plasma (>200,000 units transfused), nor to pooled PLT concentrates. CONCLUSION: The proportion of TRALI cases related to plasma-rich components was lower than previously described.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".