Safety of influenza vaccination during pregnancy: a systematic review
Bibliographic record
Abstract
OBJECTIVE: We conducted a systematic review to evaluate associations between influenza vaccination during pregnancy and adverse birth outcomes and maternal non-obstetric serious adverse events (SAEs), taking into consideration confounding and temporal biases. METHODS: Electronic databases (Ovid MEDLINE ALL, Embase Classic+Embase and the Cochrane Central Register of Controlled Trials) were searched to June 2021 for observational studies assessing associations between influenza vaccination during pregnancy and maternal non-obstetric SAEs and adverse birth outcomes, including preterm birth, spontaneous abortion, stillbirth, small-for-gestational-age birth and congenital anomalies. Studies of live attenuated vaccines, single-arm cohort studies and abstract-only publications were excluded. Records were screened using a liberal accelerated approach initially, followed by a dual independent approach for full-text screening, data extraction and risk of bias assessment. Pairwise meta-analyses were conducted, where two or more studies met methodological criteria for inclusion. The Grading of Recommendations, Assessment, Development and Evaluation approach was used to assess evidence certainty. RESULTS: Of 9443 records screened, 63 studies were included. Twenty-nine studies (24 cohort and 5 case-control) evaluated seasonal influenza vaccination (trivalent and/or quadrivalent) versus no vaccination and were the focus of our prioritised syntheses; 34 studies of pandemic vaccines (2009 A/H1N1 and others), combinations of pandemic and seasonal vaccines, and seasonal versus seasonal vaccines were also reviewed. Control for confounding and temporal biases was inconsistent across studies, limiting pooling of data. Meta-analyses for preterm birth, spontaneous abortion and small-for-gestational-age birth demonstrated no significant associations with seasonal influenza vaccination. Immortal time bias was observed in a sensitivity analysis of meta-analysing risk-based preterm birth data. In descriptive summaries for stillbirth, congenital anomalies and maternal non-obstetric SAEs, no significant association with increased risk was found in any studies. All evidence was of very low certainty. CONCLUSIONS: Evidence of very low certainty suggests that seasonal influenza vaccination during pregnancy is not associated with adverse birth outcomes or maternal non-obstetric SAEs. Appropriate control of confounding and temporal biases in future studies would improve the evidence base.
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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 | 0.014 | 0.058 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.011 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".