National Consensus Statements for the Prevention of Maternal Rhesus D Alloimmunization and Management of Alloimmunized Pregnancies: A Modified Delphi Process
Bibliographic record
Abstract
OBJECTIVES: National stakeholders developed guidance statements regarding controversial aspects of perinatal testing and management of pregnancies at risk of or affected by alloimmunization. The objective was to create national, standardized recommendations to guide testing practices, reduce unnecessary testing, optimize resources, and improve patient care. METHODS: A total of 46 multidisciplinary Canadian experts participated in an iterative Delphi process to reach consensus on 47 practices regarding all aspects of screening and management of pregnant persons at risk of alloimmunization. The panel rated their agreement on a 5-point Likert scale. After each round, panellists voted again on the statements until consensus was achieved, defined as a Cronbach α >0.95 in a maximum of 3 voting rounds. Fifteen of the 47 statements pertaining to high-risk obstetrical scenarios are presented. RESULTS: A total of 46 experts completed all rounds of voting. Consensus was achieved after 3 survey rounds (Cronbach α = 0.94) for all statements. The 15 statements reaching consensus addressed general issues pertinent to the evaluation of the high-risk patient, including testing for clinically significant antibodies (e.g., Kell), antibody titration frequency, paternal phenotyping, fetal genotyping, multidisciplinary care, and administration of RhIG following clinical situations such as ectopic or molar pregnancy and after invasive fetal testing or therapy. CONCLUSIONS: The consensus document provides guidance regarding best practices for prevention and management of alloimmunization to RhD and clinically significant antibodies to optimize RhIG usage and support clinical units. To effect practice change, knowledge translation of this consensus will require a broad educational program involving clinical offices, hospital emergency departments, and birthing units.
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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 | 0.210 | 0.163 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".