Vitamin K Antagonists for Pregnant Women With Antiphospholipid Antibodies: A Scoping Review
Bibliographic record
Abstract
OBJECTIVE: To describe characteristics of published research on the safety and efficacy of vitamin K antagonists (VKA) for pregnant patients with antiphospholipid antibodies (aPL), including their methodological characteristics and knowledge gaps. METHODS: This study followed the Joanna Briggs Institute methodology for scoping reviews and used the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews protocol system. Studies were primarily identified through searching electronic databases including MEDLINE, Embase, Web of Science, and the Cochrane Central Register of Controlled Trials. Study characteristics and outcomes were reported and described using customized charting tables. RESULTS: Of 1528 publications, 17 remained in the final analysis. These reported up to 190 VKA-treated aPL-positive pregnancies diagnosed as antiphospholipid syndrome (APS); pregnancy cases were likely overlapping in some publications. In the 17 reports, there were 723 individuals in comparison groups, including healthy pretreatment pregnancies and women with APS treated with standard therapies without VKA. However, only 4 (23.5%) of the 17 publications stated a study objective focusing on VKA use, of which only one was a full-length article. In addition, information on VKA doses, disease diagnostic criteria, and the long-term outcomes of offspring were largely absent. CONCLUSION: The current evidence is insufficient to assess VKA efficacy and safety profiles in aPL-positive pregnant patients. Studies with a defined focus on VKA use in this population are lacking, and reporting of key information is not consistent. The relative lack of knowledge of VKA use in pregnant women with APS is concerning, and efficacy and safety questions remain.
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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 | 0.021 | 0.083 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.010 |
| Bibliometrics | 0.026 | 0.020 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".