The selection and preparation of red cell components for intrauterine transfusion: A national survey
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: The practice regarding the selection and preparation of red blood cells (RBCs) for intrauterine transfusion (IUT) is variable reflecting historical practice and expert opinion rather than evidence-based recommendations. The aim of this survey was to assess Canadian hospital blood bank practice with respect to red cell IUT. MATERIALS AND METHODS: A survey was sent to nine hospital laboratories known to perform red cell IUT. Questions regarding component selection, processing, foetal pre-transfusion testing, transfusion administration, documentation and traceability were assessed. RESULTS: The median annual number of IUTs performed in Canada was 109 (interquartile range, 103-118). RBC selection criteria included allogeneic, Cytomegalovirus seronegative, irradiated, fresh units with most sites preferentially providing HbS negative, group O, RhD negative, Kell negative and units lacking the corresponding maternal antibody without extended matching to the maternal phenotype. Red cell processing varied with respect to target haematocrit, use of saline reconstitution (n = 4), use of an automated procedure for red cell concentration (n = 1) and incorporation of a wash step (n = 2). Foetal pre-transfusion testing uniformly included haemoglobin measurement, but additional serologic testing varied. A variety of strategies were used to link the IUT event to the neonate post-delivery, including the creation of a unique foetal blood bank identifier at three sites. CONCLUSION: This survey reviews current practice and highlights the need for standardized national guidelines regarding the selection and preparation of RBCs for IUT. This study has prompted a re-examination of priorities for RBC selection for IUT and highlighted strategies for transfusion traceability in this unique setting.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".