Early pregnancy outcomes following COVID-19 vaccination and SARS-CoV-2 infection: a national population-based matched cohort study
Bibliographic record
Abstract
Abstract There are limited data regarding the safety of COVID-19 vaccines in early pregnancy. This may contribute to vaccine hesitancy in people who are pregnant, or who are planning pregnancy. We conducted a population-level matched cohort study assessing associations between COVID-19 vaccination and miscarriage (pregnancy loss prior to 20 weeks gestation) and ectopic pregnancy. We used electronic health records of all female residents in Scotland who were vaccinated between 6 weeks preconception and 19 weeks 6 days gestation (for miscarriage; n = 18,780) or 2 weeks 6 days gestation (for ectopic; n = 10,570). Primary analyses used unvaccinated women from the pre-pandemic period as controls (historical controls) matched (3:1) on maternal age, gestational age at vaccination, and season of conception; with adjustment for maternal deprivation level, rural/urban status and clinical vulnerability. Supplementary analyses used unvaccinated women from the pandemic period as controls (contemporary controls). Analyses of outcomes following SARS-CoV-2 infection were undertaken with infection rather than vaccination as the exposure. Following COVID-19 vaccination, the rate of miscarriage was 9.1% (n = 1,716) and ectopic pregnancy 1.2% (n = 126). Primary analyses found no association between vaccination and miscarriage (adjusted Odds Ratio [aOR] = 1.02, 95% Confidence Interval [CI] = 0.96–1.09) or ectopic pregnancy (aOR = 1.13, 95% CI = 0.92–1.38). Primary analyses also found no association between SARS-CoV-2 infection and miscarriage or ectopic pregnancy. Results of supplementary analyses were similar to primary analyses. Given that SARS-CoV-2 infection in later pregnancy carries substantial risks to women and babies, our findings support current recommendations that vaccination remains the safest way for pregnant women to protect themselves and their babies from COVID-19.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".