Association between Birth Order and Emergency Room Visits and Acute Hospital Admissions following Pediatric Vaccination: A Self-Controlled Study
Bibliographic record
Abstract
OBJECTIVE: We investigated the association between a child's birth order and emergency room (ER) visits and hospital admissions following 2-,4-,6- and 12-month pediatric vaccinations. METHODS: We included all children born in Ontario between April 1(st), 2006 and March 31(st), 2009 who received a qualifying vaccination. We identified vaccinations, ER visits and admissions using health administrative data housed at the Institute for Clinical Evaluative Sciences. We used the self-controlled case series design to compare the relative incidence (RI) of events among 1(st)-born and later-born children using relative incidence ratios (RIR). RESULTS: For the 2-month vaccination, the RIR for 1(st)-borns versus later-born children was 1.37 (95% CI: 1.19-1.57), which translates to 112 additional events/100,000 vaccinated. For the 4-month vaccination, the RIR for 1(st)-borns vs. later-borns was 1.70 (95% CI: 1.45-1.99), representing 157 additional events/100,000 vaccinated. At 6 months, the RIR for 1(st) vs. later-borns was 1.27 (95% CI: 1.09-1.48), or 77 excess events/100,000 vaccinated. At the 12-month vaccination, the RIR was 1.11 (95% CI: 1.02-1.21), or 249 excess events/100,000 vaccinated. CONCLUSIONS: Birth order is associated with increased incidence of ER visits and hospitalizations following vaccination in infancy. 1(st)-born children had significantly higher relative incidence of events compared to later-born children.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".