Current problems and future directions of transfusion‐induced alloimmunization: summary of an NHLBI working group
Bibliographic record
Abstract
In April 2010, a working group sponsored by the National Heart, Lung, and Blood Institute was assembled to identify research strategies to improve our understanding of alloimmunization caused by the transfusion of allogeneic blood components and to evaluate potential approaches to both reduce its occurrence and manage its effects. Significant sequelae of alloimmunization were discussed and identified, including difficulties in maintaining chronic transfusion of red blood cells and platelets, hemolytic disease of the newborn, neonatal alloimmune thrombocytopenia, and rejection of transplanted cells and tissues. The discussions resulted in a consensus that identified key areas of future research and developmental areas, including genetic and epigenetic recipient factors that regulate alloimmunization, biochemical specifics of transfused products that affect alloimmunization, and novel technologies for high-throughput genotyping to facilitate extensive and efficient antigen matching between donor and recipient. Additional areas of importance included analysis of unappreciated medical sequelae of alloimmunization, such as cellular immunity and its effect upon transplant and autoimmunity. In addition, support for research infrastructure was discussed, with an emphasis on encouraging collaboration and synergy of animal models biology and human clinical research. Finally, training future investigators was identified as an area of importance. In aggregate, this communication provides a synopsis of the opinions of the working group on the above issues and presents both a list of suggested priorities and the rationale for the topics of focus. The areas of research identified in this report represent potential fertile ground for the medical advancement of preventing and managing alloimmunization in its different forms and mitigating the clinical problems it presents to multiple patient populations.
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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 | 0.029 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".