Increased emergency room visits or hospital admissions in females after 12-month MMR vaccination, but no difference after vaccinations given at a younger age
Bibliographic record
Abstract
BACKGROUND: Previous studies have suggested that a child's sex may be a predictor of vaccine reactions. METHODS: We used a self-controlled case series design, an extension of retrospective cohort methodology which controls for fixed confounders using a conditional Poisson modeling approach. We compared a risk period immediately following vaccination to a control period farther removed from vaccination in each child and estimated the relative incidence of emergency room visits and/or hospital admissions following the 2-, 4-, 6-, and 12-month vaccinations to investigate the effect of sex on relative incidence. All infants born in Ontario, Canada between April 1, 2002 and March 31, 2009 were eligible for study inclusion. RESULTS: In analyses combining immunizations at 2, 4 and 6 months and examining these vaccinations separately, there was no significant relationship between the relative incidence of an event and sex of the child. At 12 months, we observed a significant effect of sex, with female sex being associated with a significantly higher relative incidence of events (P=0.0027). The relative incidence ratio (95% CI) comparing females to males following the 12-month vaccination was 1.08 (1.03 to 1.14), which translates to 192 excess events per 100,000 females vaccinated compared to the number of events that would have occurred in 100,000 males vaccinated. CONCLUSIONS: As the MMR vaccine is given at 12 months of age in Ontario, our findings suggest that girls may have an increased reactogenicity to the MMR vaccine which may be indicative of general sex differences in the responses to the measles virus.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".