Prenatal exposure to the 2009 pandemic H1N1 influenza vaccine on health outcomes in children
Bibliographic record
Abstract
IntroductionDuring the 2009 H1N1 pandemic, less than half of pregnant women in Ontario received the recommended influenza vaccine. Commonly-cited reasons for low vaccine uptake include misconceptions about the possible impact of maternal influenza infection and vaccine safety. Providing data on previously understudied pediatric health outcomes may help increase vaccine uptake. Objectives and ApproachWe conducted a retrospective cohort study of all live births from November 2nd, 2009 to October 31st, 2010 using the BORN Ontario province-wide birth registry containing information on H1N1 vaccination. These data were deterministically/probabilistically linked with several health administrative databases held at the Institute for Clinical Evaluative Sciences to ascertain specific immune-related pediatric health outcomes and health services utilization over 5 years of follow-up. Negative binomial regression models were used to evaluate the association between prenatal H1N1 vaccination and outcomes. Stabilized inverse probability of treatment weights (sIPTW) derived from the propensity scores were used to adjust for potential confounding. ResultsThe study cohort included 104,310 eligible infants, 31,310 (30%) of whom were born to H1N1-vaccinated women. Median follow-up time was 5 years. Using sIPTWs we were able to achieve good balance of baseline measured covariates across exposure groups, with no absolute standardized differences larger than 7%. The sIPTW-adjusted analyses indicated no significant associations between prenatal exposure to H1N1 vaccination and upper respiratory infections (adjusted rate ratio [aRR] 1.01; 95% confidence interval [CI] 0.98-1.03), lower respiratory infections (aRR 1.00; 95%CI 0.96-1.04), otitis media (aRR 1.04; 95%CI 1.00-1.07), all infections (aRR 1.00; 95%CI 0.98-1.03), and rates of urgent and in-patient health services utilization (aRR 1.00; 95%CI 0.98-1.02). Conclusion/ImplicationsOur primary findings suggest there are no associations between prenatal exposure to H1N1 vaccination and (1) the development of several immune-related health outcomes in children; (2) rates of health services utilization. Furthermore, our study provides new evidence on the long-term safety of influenza vaccination during pregnancy, which is currently lacking.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".