Safety of COVID-19 vaccines in pregnancy: a Canadian National Vaccine Safety (CANVAS) Network study
Bibliographic record
Abstract
Abstract Background Pregnant individuals have been receiving COVID-19 vaccines following pre-authorization clinical trials in non-pregnant people. This study aimed to determine significant health events amongst pregnant females after COVID-19 vaccination, compared with unvaccinated pregnant controls and vaccinated non-pregnant individuals. Methods Study participants were pregnant and non-pregnant females aged 15-49 years who had received any COVID-19 vaccine, and pregnant unvaccinated controls. Participants reported significant health events occurring within seven days of vaccination. We employed multivariable logistic regression to examine significant health events associated with mRNA vaccines. Findings Overall 226/5,597(4.0%) vaccinated pregnant females reported a significant health event after dose one of an mRNA vaccine, and 227/3,108(7.3%) after dose two, compared with 11/339(3.2%) pregnant unvaccinated females. Pregnant vaccinated females had an increased odds of a significant health event after dose two of mRNA-1273 (aOR 4.4,95%CI 2.4-8.3) compared to pregnant unvaccinated controls, but not after dose one of mRNA-1273 or any dose of BNT162b2. Pregnant females had decreased odds of a significant health event compared to non-pregnant females after both dose one (aOR 0.63,95%CI 0.55-0.72) and dose two (aOR 0.62,95%CI 0.54-0.71) of mRNA vaccination. There were no significant differences in any analyses when restricted to events which led to medical attention. Interpretation COVID-19 mRNA vaccines have a good safety profile in pregnancy. Rates of significant health events were higher after dose two of mRNA-1273 compared with unvaccinated controls, with no difference when considering events leading to medical consultation. Rates of significant health events were lower in pregnant females than similarly aged non-pregnant individuals. Funding This work was supported by the COVID-19 Vaccine Readiness funding from the Canadian Institutes of Health Research and the Public Health Agency of Canada CANVAS grant number CVV-450980 and by funding from the Public Health Agency of Canada, through the Vaccine Surveillance Reference Group and the COVID-19 Immunity Task Force.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".