Monitoring of prenatal patients using a combined antibody titre for Rh and non‐Rh antibodies
Bibliographic record
Abstract
OBJECTIVES: This was a laboratory exercise designed to determine whether combined antibody titrations in the presence of multiple antibodies achieve a critical level earlier or at the same time as antibodies having individual antibody titrations. BACKGROUND: Management of haemolytic disease of the fetus and newborn involves monitoring maternal antibody concentration by antibody titration. Separate titrations are generally performed for each antibody. METHOD: Thirty-one samples containing combinations of two different Rh and/or non-Rh antibodies were examined with separate titres for each antibody and one single combined titration. RESULTS: Of 31 samples, 19 (61.3%) showed an increased combined titre. Of 12 samples that showed no increase, 10 contained a separate titre of <1 for either one or both antibodies. Where both antibodies had a separate titre of ≥1, 15 of 17 (88.2%) showed an increased combined titre. In contrast to the separate titration method, no decrease in titre level was observed using the combined method. CONCLUSION: Where two antibodies are present, titrations performed by a combined method will produce titre levels equal to or higher than antibodies titred individually. Therefore, a combined titration can be expected to reach a critical titre level as early as, or earlier in gestation than, antibodies monitored by a single titration method. Further studies relating fetal outcomes to titration methodology would be valuable in determining the validity of this approach for prenatal management. Cost-effectiveness of this approach to prenatal screening should also be assessed.
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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) | 0.001 | 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".