Does adding hydroxychloroquine to empiric treatment improve the live birth rate in refractory obstetrical antiphospholipid syndrome? A systematic review
Bibliographic record
Abstract
PROBLEM: The current standard prevention of obstetric complications in patients with antiphospholipid antibody syndrome (APS) is the use of combination low-dose aspirin and low molecular weight heparin. However, 20-30% of women still experience refractory obstetrical APS. Hydroxychloroquine (HCQ) is an immunomodulatory agent that has been shown in laboratory studies to decrease thrombosis risk, support placentation, and minimize the destructive effects of antiphospholipid antibodies. The objective of this study was to evaluate the risk of pregnancy loss upon treatment with HCQ among women with refractory obstetrical APS. METHOD OF STUDY: A systematic review was conducted according to PRISMA guidelines. Studies that evaluated the use of HCQ during pregnancy in women with primary APS were included. The primary outcomes of interest were live birth and pregnancy losses after treatment with HCQ. RESULTS: Twelve studies met inclusion criteria. Three retrospective cohort studies demonstrated improved live birth rate, and four studies demonstrated a reduction in pregnancy loss rate. Two case reports also demonstrated a benefit in the use of HCQ compared to previous obstetrical outcomes. CONCLUSIONS: Our findings suggest a significant benefit of HCQ in addition to aspirin and heparin for patients with APS to mitigate the risk of antiphospholipid antibody mediated obstetrical complications. Randomized controlled trials with standardized patient selection criteria need to be conducted to corroborate these findings.
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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 | 0.005 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.007 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".