Transfusion‐related lung injury in children: a case series and review of the literature
Bibliographic record
Abstract
BACKGROUND: Transfusion-related acute lung injury (TRALI) is the leading cause of transfusion-related mortality. The majority of the literature involves adult patients. The main objective of this study was to characterize the demographic features, clinical presentation, patient outcomes, and antibody profiles of TRALI patients reported to the Canadian Blood Service (CBS) and to assess similarities and differences between adult and pediatric TRALI cases. STUDY DESIGN AND METHODS: A retrospective review of cases of TRALI submitted to the CBS from 2001 to 2011 was performed. Information collected included recipient demographics, event details, blood component transfused, morbidity and mortality data, and donor antibody results. RESULTS: A total of 284 cases of definite, possible, or probable TRALI were reported. Six percent (n = 17) occurred in children. There were no significant differences between pediatric or adult patients with TRALI. Most of the children who presented with TRALI were either teenagers or less than 1 year of age. The incident rate of reported TRALI cases in Canada per 100,000 red blood cell transfusions was estimated at 5.58 for children and 3.75 for adults. CONCLUSIONS: This study is the largest case series of reported TRALI cases in children. Crude modeling suggests that the incidence of TRALI in children is similar to that of adults. Although the numbers are small, there do not appear to be differences in presentation or outcome between adults and children with TRALI. TRALI is associated with significant morbidity and mortality and pediatricians need to consider this diagnosis in children who experience respiratory distress after transfusions.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".