Neonatal intracardiac thrombosis secondary to transplacental transfer of maternal antiphospholipid antibodies-a case report and review of the literature
Bibliographic record
Abstract
Background: Maternal antiphospholipid immunoglobulin (Ig) G antibodies can cross the placenta, placing neonates at uncertain risk for thrombosis. There are no previous reports of neonatal intracardiac thrombosis (ICT) in the context of anticardiolipin antibodies (aCL). Key Clinical Question: What were the clinical manifestations, management, and outcomes for a mother and her child with ICT secondary to presumed transplacental transfer of aCL? Clinical Approach: A 2-week-old female presented with reduced feeding and was found to be poorly perfused with significant lactic acidosis. A mobile mass was noted near the left atrial appendage on the echocardiogram and confirmed on cardiac magnetic resonance imaging. Magnetic resonance imaging of the brain was normal, with no evidence of stroke. The aCL IgG titers returned highly positive for the infant (115.3 IgG phospholipid (GPL)-Unit [U]/mL) and mother (>160 GPL-U/mL; >99th percentile local reference is ≥20 GPL-U/mL). There were no other overt risk factors for thrombosis. The infant received 6 months of enoxaparin until aCL normalized. There remains a small calcified thrombus adherent to the left atrial wall. At 2 years old, the child remains healthy with no cardiac, neurologic, nor thrombotic sequelae. Conclusion: This is the first report of neonatal ICT presumed secondary to maternal aCL. The outcome was favorable with anticoagulation management. Further research is needed in the area of transplacental antiphospholipid antibody transfer, identification of neonates at risk, and optimal clinical management.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".