Bibliographic record
Abstract
Background Intrauterine transfusion ( IUT ) is a treatment for fetal anemia. This technique involves ultrasound guided needle placement followed by transfusion of a specially prepared blood component. The most common indications include hemolytic disease of the fetus and newborn ( HDFN ) and prenatal infection. Methods The literature was reviewed, and blood component characteristics and preparatory techniques identified. An international survey of IUT was conducted. Results Component preparation for IUT differs from preparation for other transfusions. Differences relate to unique characteristics of the fetus including a small blood volume, invasive access for transfusion and immune deficiency. The techniques for preparation of red blood cells ( RBC ) are variable with limited evidence. Most use fresh concentrated RBC . Irradiation is uniformly recommended. RBC that are antigen negative for the maternal alloantibody are provided, and the product is selected or modified to minimize risk for cytomegalovirus transmission. Selection of ABO group and the degree of additional prophylactic phenotype matching are variable. While maternal RBC transfusion may be used, compatible allogeneic RBC are more common. For maternal antibodies to high prevalence antigens rare phenotype deglycerolized RBC may be used. There are challenges in providing RBC for IUT . Pre and post transfusion blood samples must be correctly managed in the medical record. Hemovigilance requires that both the fetus and the mother be documented as recipients. Preparation may be urgent, and sterile technique is required. Records of IUT must be conveyed to neonatal care providers as the transfused blood may mask the true blood group for weeks to months post transfusion, and component modifications may be required for any postnatal transfusion in neonates who were treated with IUT.
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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 | 0.001 |
| 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".