Preconception contraceptive use and miscarriage: prospective cohort study
Bibliographic record
Abstract
Objectives: To evaluate the association between preconception contraceptive use and miscarriage. Design: Prospective cohort study. Setting: Residents of the United States of America or Canada, recruited from 2013 until the end of 2022. Participants: 13 460 female identified participants aged 21-45 years who were planning a pregnancy were included, of whom 8899 conceived. Participants reported data for contraceptive history, early pregnancy, miscarriage, and potential confounders during preconception and pregnancy. Main outcome measure: Miscarriage, defined as pregnancy loss before 20 weeks of gestation. Results: Preconception use of combined and progestin-only oral contraceptives, hormonal intrauterine devices, copper intrauterine devices, rings, implants, or natural methods was not associated with miscarriage compared with use of barrier methods. Participants who most recently used patch (incidence rate ratios 1.34 (95% confidence interval 0.81 to 2.21)) or injectable contraceptives (1.44 (0.99 to 2.12)) had higher rates of miscarriage compared with recent users of barrier methods, although results were imprecise due to the small numbers of participants who used patch and injectable contraceptives. Conclusions: Use of most contraceptives before conception was not appreciably associated with miscarriage rate. Individuals who used patch and injectable contraceptives had higher rates of miscarriage relative to users of barrier methods, although these results were imprecise and residual confounding was possible.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".