Fetal and neonatal alloimmune thrombocytopenia: recommendations for evidence‐based practice, an international approach
Bibliographic record
Abstract
Fetal and neonatal alloimmune thrombocytopenia (FNAIT) may result in severe bleeding, particularly fetal and neonatal intracranial haemorrhage (ICH). As a result, FNAIT requires prompt identification and treatment; subsequent pregnancies need close surveillance and management. An international panel convened to develop evidence-based recommendations for diagnosis and management of FNAIT. A rigorous approach was used to search, review and develop recommendations from published data for: antenatal management, postnatal management, diagnostic testing and universal screening. To confirm FNAIT, fetal human platelet antigen (HPA) typing, using non-invasive methods if quality-assured, should be performed during pregnancy when the father is unknown, unavailable for testing or heterozygous for the implicated antigen. Women with a previous child with an ICH related to FNAIT should be offered intravenous immunoglobulin (IVIG) infusions during subsequent affected pregnancies as early as 12 weeks gestation. Ideally, HPA-selected platelets should be available at delivery for potentially affected infants and used to increase the neonatal platelet count as needed. If HPA-selected platelets are not immediately available, unselected platelets should be transfused. FNAIT studies that optimize antenatal and postnatal management, develop risk stratification algorithms to guide management and standardize laboratory testing to identify high risk pregnancies are needed.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".