Health Outcomes in Young Children Following Pertussis Vaccination During Pregnancy
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Maternal immunization with tetanus, diphtheria, and acellular pertussis vaccine (Tdap) is routinely recommended in many countries as a strategy to protect young infants against severe pertussis infection; few studies have assessed whether prenatal exposure to the vaccine is associated with any longer-term adverse health effects in children. We evaluated the long-term safety of exposure to Tdap vaccination during pregnancy. METHODS: Population-based retrospective cohort study conducted in Ontario, Canada using multiple linked province-wide health administrative databases. All live births between April 2012 and March 2017 were included, and children were followed for up to 6 years to ascertain study outcomes. Children exposed to prenatal Tdap were propensity score matched to unexposed children at a 1:5 ratio. Tdap vaccination during pregnancy was ascertained by using vaccine-specific fee codes. Immune-related (infectious diseases, asthma) and nonimmune-related (neoplasm, sensory disorders) outcomes and a nonspecific morbidity outcome (urgent or inpatient health service use) were evaluated from birth to end of follow-up. RESULTS: Of 625 643 live births, 12 045 (1.9%) were exposed to Tdap in utero. There were no significant increased risks of adverse childhood outcomes and prenatal Tdap exposure; however, we observed inverse associations (adjusted incidence rate ratio [95% confidence interval]) with upper respiratory infections (0.94 [0.90-0.99]), gastrointestinal infections (0.85 [0.79-0.91]), and urgent and inpatient health service use (0.93 [0.91-0.96]). CONCLUSIONS: Exposure to Tdap vaccination in pregnancy was not associated with any increased risk of adverse health outcomes in early childhood, supporting the long-term safety of Tdap administration in pregnancy.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".