Early intrauterine transfusion in severe red blood cell alloimmunization
Bibliographic record
Abstract
OBJECTIVE: To determine perinatal outcome in pregnancies with early severe red blood cell (RBC) alloimmunization. METHODS: This was a retrospective analysis of 30 patients requiring their first intrauterine transfusion (IUT) at < 22 weeks of gestation. Timing of the first IUT was based on evaluation of either the middle cerebral artery peak systolic velocity (MCA-PSV) or development of ascites. RESULTS: Thirty-three per cent of the patients had experienced a previous intrauterine fetal death as a result of RBC alloimmunization. Of these alloimmunized pregnancies, 26 (87%) were associated with anti-D, four (13%) with anti-Kell and 12 had more than one antibody type involved. The antibody titers before the first IUT ranged from 1:128 to 1:8024. All fetuses were severely anemic before the first IUT with a median hemoglobin (Hb) level of 37 (range, 3-81) g/L. The nine hydropic fetuses had a lower Hb level compared with non-hydropic fetuses (median 15 g/L vs. 42 g/L, P = 0.016). However, 15 (71%) non-hydropic fetuses had an Hb level of < 50 g/L before the first IUT. The median gestational age at the first IUT was 20.4 (range, 16-22) weeks, and between one and nine transfusions were needed during pregnancy. Transfusion was via the intrahepatic vein (IHV) (n = 19), umbilical vein (n = 6) or umbilical artery (n = 2), or was intracardiac (n = 2) or intraperitoneal (n = 1). Overall perinatal survival rate was 80% and did not differ between hydropic and non-hydropic fetuses. Median gestation at delivery, after exclusion of six intrauterine fetal deaths, was 36.7 (range, 27.8-38.4) weeks. CONCLUSIONS: In early severe RBC alloimmunization, fetuses can be severely anemic without hydrops, and prognosis cannot be predicted by the presence or absence of hydrops. Early IUT followed by serial transfusions is associated with a perinatal survival rate of about 80%.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".