HLA alloimmunization against platelet transfusions: pathophysiology, significance, prevention and management
Bibliographic record
Abstract
Approximately five decades ago, alloimmunization to human leukocyte antigens (HLA) and platelet refractoriness were recognized as potentially serious complications of platelet transfusions. The mechanisms that result in stimulating immunity against blood products are still incompletely understood but are related to both the composition of the donor product transfused and the immune status of the recipient. Based on murine studies of platelet immunity, platelets are inherently immunogenic and there are at least two independent levels of immunoregulation against platelet transfusions. The first level resides within the recipient and is related to antigen processing/presentation events and CD8+ T cell-mediated immunosuppression. The second level relates to the donor product and includes donor antigen presenting cells (APC) levels as well as age-induced changes in donor APC and/or platelets. Implementation of pre-storage leukoreduction of cellular blood components led to a marked reduction in platelet alloimmunization and its dreaded complication, platelet refractoriness. Platelet refractoriness is usually managed by transfusion of matched platelets, selected according to one of the many published methods. It is unclear which of these methods is superior, and given the difficulty of obtaining a perfectly matched product, perhaps the most logical approach is to use a combination of selection strategies. This review discusses the various aspects of platelet alloimmunization and the clinical consequences that may result. It highlights how animal studies have shed light on the immune mechanisms responsible for allogeneic platelet immunity and immunomodulation and reviews relevant literature on clinical and laboratory manifestations of immune platelet refractoriness.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".