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Record W236020377 · doi:10.2450/2014.0083-14

RhD and haematopoietic transplantation.

2014· letter· en· W236020377 on OpenAlexaff
David Allan, Elianna Saidenberg

Bibliographic record

VenuePubMed · 2014
Typeletter
Languageen
FieldMedicine
TopicBlood groups and transfusion
Canadian institutionsOttawa Hospital
Fundersnot available
KeywordsTransplantationMedicineImmunologyContext (archaeology)Haemolytic diseasePregnancyDiseaseIsoantibodiesFetusAntibodyIntensive care medicineBiologyInternal medicine

Abstract

fetched live from OpenAlex

RhD antigens are highly antigenic and anti-D antibodies are known to cause haemolytic disease of the foetus and newborn and acute haemolytic transfusion reactions. However, the importance of the D antigen in haematopoietic progenitor cell (HPC) transplantation has been less well defined. In this issue of Blood Transfusion Cid et al.1 report a review of outcomes following RhD mismatched and incompatible HPC transplantation that provides greater insight regarding clinical outcomes and possible implications for transfusion practices. They conclude that D antigen-incompatible HPC transplantation is not likely to result in serious clinical consequences although the persistence of anti-D antibodies may be associated with worse outcomes in some settings. More information is needed to understand how transplant centres adapt their transfusion practices in RhD incompatible and mismatched transplants. Importantly, there may be certain settings in which RhD mismatches warrant special consideration in the context of allogeneic HPC transplantation. Prior to the introduction of Rh immunoglobulin as effective prevention, haemolytic disease of the foetus and newborn was an important cause of neonatal mortality and morbidity. Typically women are allo-immunised through pregnancy or transfusion. The work of Cid et al.1 suggests that HPC transplantation may be another means of immunisation with up to 10% of RhD-mismatched transplants resulting in development of anti-D. In a woman requiring HPC transplant whose fertility is likely to be preserved following the transplant or when implantation of frozen embryos following transplantation is likely to lead to a viable pregnancy2, RhD mismatching may be a relevant consideration affecting donor selection, in the fortunate context in which more than one HLA-matched donor is available. It is unlikely that RhD mismatching would have a negative affect on ability of transfusion services to supply safe products for transfusion. Although highly allo-immunised patients can pose a significant challenge to transfusion services for patients undergoing transplantation, approximately 10% of blood donors are RhD-negative and providing antigen-negative packed red blood cell units for transfusion to a patient who is D-immunised should not be a problem for most transfusion services unless patients return to remote locations where access to blood products is more limited. Consequently the presence of anti-D prior to transplantation or its development in the post-transplant period should not be a key consideration in planning transplants. The ongoing presence of anti-D or the re-emergence of anti-D antibodies in a patient immunised prior to transfusion may, however, be a harbinger of other adverse events unrelated to transfusion issues but that are related to persistent host immunity. Cid et al.1 (see Table III) cite four cases in which a transplant recipient mounted a response to the donor’s RhD-positive red cells. This finding indicates mixed chimerism which can be associated with late graft failure and/or relapse. Given the difficulty of finding compatible donors for patients requiring HPC transplantation, it is unlikely that RhD antigen differences between donor and recipient will be a major consideration in donor selection3. However, improved understanding of post-transplant immunisation and what it tells us about host immunity may enable important improvements in our ability to offer safer and more effective options for HPC transplantation and for transfusions to such patients.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.080
Threshold uncertainty score0.589

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.020
GPT teacher head0.206
Teacher spread0.186 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

Quick stats

Citations0
Published2014
Admission routes1
Has abstractyes

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