Antiplatelet drugs for prevention of pre-eclampsia and its consequences: systematic review
Bibliographic record
Abstract
OBJECTIVE: To assess the effectiveness and safety of antiplatelet drugs for prevention of pre-eclampsia and its consequences. DESIGN: Systematic review. DATA SOURCES: Register of trials maintained by Cochrane Pregnancy and Childbirth Group, Cochrane Controlled Trials Register, and Embase. INCLUDED STUDIES: Randomised trials involving women at risk of pre-eclampsia, and its complications, allocated to antiplatelet drug(s) versus placebo or no antiplatelet drug. MAIN OUTCOME MEASURES: Pre-eclampsia, preterm birth, fetal or neonatal death, and small for gestational age baby. Studies were assessed for quality of concealment of allocation and losses to follow up. RESULTS: 39 trials (30 563 women) were included, and 45 trials (>3000 women) excluded. Use of antiplatelet drugs was associated with a 15% reduction in the risk of pre-eclampsia (32 trials, 29 331 women; relative risk 0.85, 95% confidence interval 0.78 to 0.92; number needed to treat 100, 59 to 167). There was also an 8% reduction in the risk of preterm birth (23 trials, 28 268 women; 0.92, 0.88 to 0.97; 72, 44 to 200), and a 14% reduction in the risk of fetal or neonatal death (30 trials, 30 093 women; 0.86, 0.75 to 0.98; 250, 125 to >10 000) for women allocated antiplatelet drugs. Small for gestational age babies were reported in 25 trials (20 349 women), with no overall difference between the groups (relative risk 0.92, 0.84 to 1.01). There were no significant differences in other measures of outcome. CONCLUSIONS: Antiplatelet drugs, largely low dose aspirin, have small to moderate benefits when used for prevention of pre-eclampsia.
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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 | 0.007 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.007 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".