Fetal-Neonatal Alloimmune Thrombocytopenia (FNAIT): Guidance to Reduce the Risk of Intracranial Bleeding
Bibliographic record
Abstract
Abstract Introduction FNAIT is associated with severe bleeding, especially intracranial hemorrhage (ICH), in the fetus and/or newborn. More than 75% of ICHs occur in utero and up to 50% before 32 weeks gestation. The consequences of ICH include death (35%) or serious neurological sequelae in survivors (83%). FNAIT requires prompt identification and treatment antepartum, postpartum and in subsequent pregnancies. An international panel was convened by the International Collaboration for Transfusion Medicine Guidelines (ICTMG) to develop evidence based recommendations for diagnosis and management of FNAIT. Methods The international panel consisted of specialists in adult and pediatric hematology, maternal fetal medicine (MFM), neonatology, methodology, transfusion medicine, and a patient representative. Clinical questions were developed for diagnostic testing, antenatal screening and management, and postnatal interventions. A systematic search for articles published between 1946 and June 2017 in MEDLINE, EMBASE and Cochrane was conducted. Recommendations were formulated based on the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) method which incorporates the quality of the evidence, benefits and risks, and resource utilization. Web conferences and electronic correspondence were used to discuss the results of the systematic reviews and formulate recommendations. Considerations for clinical practice such as dosing of intravenous immunoglobulin (IVIG) and corticosteroids were detailed. Electronic surveys were sent to all members to assess agreement with recommendations. The final guidance document was sent to maternal fetal, hematology and pediatric societies for comments. Results Three systematic reviews (antenatal management, postnatal management and use of laboratory investigations to identify pregnancies at risk) were developed. Antenatal recommendations: Women with FNAIT in a previous pregnancy or sisters of women with FNAIT should be referred to MFM centers. Fetal HPA typing (e.g. HPA-1a/1b) should be performed in HPA-immunized pregnant women when the paternity is unknown or the partner is heterozygous or unavailable for testing. Prenatal HPA-1 typing should preferentially be performed by a non-invasive method e.g. cell-free fetal DNA (cffDNA) in maternal plasma if adequately quality assured. Antenatal IVIG administration to the mother commencing at 12-16 weeks gestation should be offered to all women in a subsequent pregnancy with maternal fetal incompatibility who have had a previous fetus or neonate with FNAIT related ICH. For all other pregnancies with a previous neonate with FNAIT (without ICH), administering antenatal IVIG to the mother should be discussed prior to a subsequent pregnancy or when pregnancy with maternal fetal incompatibility is confirmed. If corticosteroids are used with IVIG, dexamethasone should not be used because of the associated risk of oligohydramnios. Postnatal recommendations: HPA-selected platelets should be made available at delivery for potentially affected infants to increase the neonatal platelet count. If HPA-selected platelets are not immediately available, unselected platelets should be used. In the presence of life-threatening neonatal hemorrhage such as intracranial or gastrointestinal bleeding, platelets should be transfused to maintain platelet counts above 50 to 100x109/L for at least 7 days. In the absence of life-threatening bleeding in a neonate such as intracranial or gastrointestinal bleeding, platelets should be transfused to maintain a platelet count above 30x109/L. Conclusions The intent of this guidance document developed from systematic reviews is to promote best practices in the management of FNAIT. The guideline development group developed algorithms for treatment, podcasts for physicians and patients, pamphlets for patients and a slide set to assist with the implementation of recommendations into practice. This expert panel identified key areas for future research. One is the optimal approach to antenatal management of the next affected pregnancy. Developing biomarkers of fetal severity would be critical to this endeavor. In addition, creating comprehensive screening to identify HPA-1b1b women at risk of FNAIT would advance successful prevention of this disease. Disclosures Bakchoul: German Research Society (DFG): Research Funding; Aspen Germany gGmbH, CLS Behring, Stago gGmbH: Honoraria; Robert Bosch gGmbH: Research Funding. Kjaer:Prophylix Pharma: Equity Ownership. Kjeldsen-Kragh:Prophylix Pharma: Equity Ownership. Oepkes:Towards routine HPA screening in pregnancy: Research Funding. Bussel:Uptodate: Honoraria; Rigel: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; Protalex: Consultancy; Amgen Inc.: Consultancy, Research Funding; Prophylix: Consultancy, Research Funding; Momenta: Consultancy. Arnold:Bristol Myers Squibb: Research Funding; Amgen: Consultancy, Research Funding; UCB: Consultancy; Novartis: Consultancy, Research Funding; Bristol Myers Squibb: Research Funding; UCB: Consultancy; Novartis: Consultancy, Research Funding; Amgen: Consultancy, Research Funding. Savoia:Neonatal Alloimmune Thrombocytopenia Registry of the Transfusion Outcomes Research Collaborative (TORC) Australia: Membership on an entity's Board of Directors or advisory committees.
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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 | 0.016 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.009 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".