Low-molecular-weight heparins for thromboprophylaxis and treatment of venous thromboembolism in pregnancy: a systematic review of safety and efficacy
Bibliographic record
Abstract
To assess the safety and efficacy of low-molecular-weight heparins (LMWHs) for thromboprophylaxis and treatment of venous thromboembolism (VTE) in pregnancy, a systematic review of studies to the end of 2003 was undertaken. Data on VTE recurrence and side effects were extracted and cumulative incidences of VTE and adverse effects calculated. Of 81 reports identified, 64 reporting 2777 pregnancies were included. In 15 studies (174 patients) the indication for LMWH was treatment of acute VTE, and in 61 studies (2603 pregnancies) it was thromboprophylaxis or adverse pregnancy outcome. There were no maternal deaths. VTE and arterial thrombosis (associated with anti-phospholipid syndrome) were reported in 0.86% (95% confidence interval [CI], 0.55%-1.28%) and 0.50% (95% CI, 0.28%-0.84%) of pregnancies, respectively. Significant bleeding, generally associated with primary obstetric causes, occurred in 1.98% (95% CI, 1.50%-2.57%), allergic skin reactions in 1.80% (95% CI, 1.34%-2.37%), heparin-induced thrombocytopenia in 0%, thrombocytopenia (unrelated to LMWH) in 0.11% (95% CI, 0.02%-0.32%), and osteoporotic fracture in 0.04% (95% CI, < 0.01%-0.20%) of pregnancies. Overall, live births were reported in 94.7% of pregnancies, including 85.4% in those receiving LMWH for recurrent pregnancy loss. LMWH is both safe and effective to prevent or treat VTE in pregnancy.
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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 | 0.008 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".