The Effect of Preconception-Initiated Low-Dose Aspirin on Human Chorionic Gonadotropin–Detected Pregnancy, Pregnancy Loss, and Live Birth
Bibliographic record
Abstract
BACKGROUND: A previous large randomized trial indicated that preconception-initiated low-dose aspirin (LDA) therapy did not have a positive effect on pregnancy outcomes. However, this trial was subject to nonadherence, which was not taken into account by the intention-to-treat approach. OBJECTIVE: To estimate per protocol effects of preconception-initiated LDA on pregnancy loss and live birth. DESIGN: The EAGeR (Effects of Aspirin on Gestation and Reproduction) trial was used to construct a prospective cohort for a post hoc analysis. (ClinicalTrials.gov: NCT00467363). SETTING: 4 university medical centers in the United States. PARTICIPANTS: 1227 women between the ages of 18 and 40 years who had 1 or 2 previous pregnancy losses and were attempting pregnancy. MEASUREMENTS: Adherence to LDA or placebo, assessed by measuring pill bottle weights at regular intervals during follow-up. Primary outcomes were human chorionic gonadotropin (hCG)-detected pregnancies, pregnancy losses, and live births, determined by pregnancy tests and medical records. RESULTS: Relative to placebo, adhering to LDA for 5 of 7 days per week led to 8 more hCG-detected pregnancies (95% CI, 4.64 to 10.96 pregnancies), 15 more live births (CI, 7.65 to 21.15 births), and 6 fewer pregnancy losses (CI, -12.00 to -0.20 losses) for every 100 women in the trial. In addition, compared with placebo, postconception initiation of LDA therapy led to a reduction in the estimated effects. Furthermore, effects were obtained in a minimum of 4 of 7 days per week. LIMITATION: The EAGeR trial data for this study were analyzed as observational data, thus are subject to the limitations of prospective observational studies. CONCLUSION: Per protocol results suggest that preconception use of LDA at least 4 days per week may improve reproductive outcomes for women who have had 1 or 2 pregnancy losses. Increasing adherence to daily LDA seems to be key to improving effectiveness. PRIMARY FUNDING SOURCE: National Institutes of Health.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".