Rh discrepancies caused by variable reactivity of partial and weak D types with different serologic techniques
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: RhD discrepancies between current and historical results are problematic to resolve. The investigation of 10 discrepancies is reported here. STUDY DESIGN: Samples identified were those that reacted by automated gel technology and were negative with an FDA-approved reagent. Reactivity with a commercially available panel of monoclonal anti-D was performed. Genomic DNA was evaluated for RHD alleles with multiplex RHD exon polymerase chain reaction (PCR), weak D PCR-restriction fragment length polymorphism, and RHD exon 5 and 7 sequence analyses. RESULTS: The monoclonal anti-D panel identified two samples as DVa, yet possessed the DAR allele. Two weak D Type 1 samples had a similar monoclonal anti-D profile, but only one reacted directly with one of two FDA-approved anti-D. Only two of four weak D Type 2 samples reacted directly with one FDA-approved anti-D, and their D epitope profile differed. CONCLUSIONS: The monoclonal anti-D reagents did not distinguish between partial and weak D Types 1 and 2. Weak D Types 1 and 2 do not show consistent reactivity with FDA-approved reagents and technology. To limit anti-D alloimmunization, it is recommended that samples yielding an immediate-spin tube test cutoff score of not more than 5 (i.e., < or =1+ agglutination) or a score of not more than 8 (i.e., < or =2+ hemagglutination) by gel technology be considered D- for transfusion and Rh immune globulin prophylaxis. That tube test anti-D reagents react poorly with some Weak D Types 1 and 2 red cells is problematic, inasmuch as they should be considered D+ for transfusion and prenatal care. Molecular tests that distinguish common partial and Weak D types provide the solution to resolving D antigen discrepancies.
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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 it