A possible case of recipient anti‐neutrophil and anti‐human leukocyte antigen antibody‐mediated fatal reverse transfusion‐related acute lung injury
Bibliographic record
Abstract
Abstract Background Transfusion‐related acute lung injury (TRALI) is a transfusion complication often mediated by recipient exposure to plasma from donors with human leukocyte antigen (HLA) and human neutrophil antigen (HNA) antibodies. Recipient anti‐donor HLA or HNA antibodies have rarely been implicated. Study Design and Methods Herein, we describe a case of fatal TRALI mediated by recipient anti‐HLA and anti‐HNA antibodies. Cognate antibody–antigen match was confirmed with serologic and molecular assays. Results A 69‐year‐old G5P5 female with no prior transfusion history and metastatic cholangiocarcinoma with thromboembolic complications presented with heart failure and dyspnea. She was transfused 15 ml of a unit of Fy a ‐negative red blood cells and subsequently developed acute onset dyspnea, hypoxemia, hypotension, and fever. Clinical investigations revealed bilateral infiltrates on chest X‐ray and cognate recipient HLA and HNA antibodies to donor antigens. The patient died of acute respiratory failure within 24 h of transfusion. In total, the patient had Fy a , HLA Class I, HNA, and human platelet antigen (HPA) alloantibodies. The 63‐year‐old female donor had detectable HLA class II antibodies (recipient class II genotype unavailable). Conclusion The pathophysiology of TRALI has traditionally been ascribed to underlying conditions that put the recipient at risk in combination with donor biological response modifiers. This case illustrates alternative pathogenic mediators including alloantibodies to donor HLA and HNA. Additional studies to determine the contribution and frequency of recipient alloantibodies in TRALI may inform future mitigation strategies to further reduce the incidence of TRALI, particularly in female transfusion recipients.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| 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".