The effect of aspirin on the risk of preeclampsia based on the Fetal Medicine Foundation first-trimester risk
Bibliographic record
Abstract
BACKGROUND: Aspirin reduces the risk of delivery with preterm preeclampsia among high-risk women, and such risk can be estimated in the first trimester of pregnancy using the Fetal Medicine Foundation algorithm by combining maternal factors with mean arterial pressure, uterine artery pulsatility index, and serum placental growth factor. It is unclear whether the initial risk influences the effect of aspirin. OBJECTIVE: This study aimed to estimate the effect of aspirin on preeclampsia according to first-trimester risk. STUDY DESIGN: This was a post hoc secondary analysis of the Aspirin for Evidence-Based Preeclampsia Prevention trial, which randomized participants with a first-trimester risk of preeclampsia with delivery before 37 weeks of gestation (preterm preeclampsia) of ≥1 in 100 (or 1%), based on the Fetal Medicine Foundation algorithm, to receive aspirin 150 mg or placebo daily from 11 to 14 weeks to 36 weeks of gestation. The rates of preeclampsia, preterm preeclampsia, and early preeclampsia (with delivery before 34 weeks of gestation) were calculated according to the initial Fetal Medicine Foundation risk. Among participants with high compliance (≥90% of tablets prescribed) based on regular tablet counts, the effect of aspirin was estimated according to the initial Fetal Medicine Foundation risk. Relative risks with 95% confidence intervals were calculated. RESULTS: Of 822 participants in the placebo group, those with an initial Fetal Medicine Foundation risk of ≥1 in 20 (or >5%) had an overall rate of preeclampsia (21.7%), preterm preeclampsia (8.4%), and early preeclampsia (6.4%) significantly greater than those with an initial risk of <1 in 20 (8.1%, 2.9%, and 0.3%, respectively; all with P<.01). Of 1143 participants with high compliance randomized to aspirin or placebo, aspirin was associated with a reduction in preeclampsia at any gestation (relative risk, 0.64 [95% confidence interval, 0.44-0.93]), preterm preeclampsia (relative risk, 0.24 [95% confidence interval, 0.09-0.63]), and early preeclampsia (estimated relative risk, 0.06 [95% confidence interval, 0.01-0.96]) compared with placebo. Subgroup analyses enabled the identification of a differential response according to the initial Fetal Medicine Foundation risk. Among participants with an initial risk of ≥1 in 20, an absence (0.0%) of delivery with preeclampsia up to 35 weeks of gestation was observed in those randomized to aspirin compared with 6.1% in those randomized to placebo (estimated relative risk, 0.06 [95% confidence interval, 0.01-0.94]). In addition, it was observed that aspirin did not reduce significantly the preterm preeclampsia in this subgroup (relative risk, 0.47 [95% confidence interval, 0.17-1.34]). In contrast, when the initial risk was <1 in 20, aspirin was associated with an absence of delivery with preeclampsia up to 37 weeks of gestation compared with 2.5% with placebo (estimated relative risk, 0.05 [95% confidence interval, 0.01-0.78]). CONCLUSION: The first-trimester Fetal Medicine Foundation risk of preterm preeclampsia is associated with the risks of preeclampsia, preterm preeclampsia, and early preeclampsia. The prophylactic daily use of 150 mg aspirin, with compliance of ≥90%, can prevent almost all cases of preeclampsia with delivery up to 37 weeks of gestation when the initial risk is <1 in 20 and up to 35 weeks of gestation when the initial risk is ≥1 in 20 (≥5%). Women with an initial risk of ≥1 in 20 should be closely monitored from 34 to 35 weeks of gestation as they remain at risk of late preterm preeclampsia.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".