The Role of Plasmapheresis in the Management of Severe Rhesus Incompatibility During Pregnancy: A Literature Review
Bibliographic record
Abstract
ABSTRACT Introduction To evaluate the effectiveness and safety of plasmapheresis in cases complicated by severe alloimmunization. Methods We reviewed multiple studies from databases like Medline, Embase, and Cochrane, looking specifically for research on ‘Rhesus incompatibility’, ‘plasmapheresis’, and ‘pregnancy’. After narrowing down, we included 46 studies that met our criteria to see how this treatment affected both prenatal and postnatal health. Results Out of 208 pregnancies analysed, about 22.1% sadly resulted in foetal loss, with one neonatal death. However, starting plasmapheresis as early as 3 weeks helped delay or avoid the need for Intrauterine blood transfusions in cases of severe foetal anaemia. Most of the babies born (77.4%) had positive outcomes, although many needed phototherapies after birth. Combining IVIG with plasmapheresis appears to be safe, with good postnatal outcomes. Conclusions Plasmapheresis shows promise as a treatment for severe Rhesus sensitisation, potentially reducing the need for Intrauterine transfusions and improving newborn outcomes. More studies are needed to refine treatment protocols and confirm these early findings.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".