Assessing the risk of intussusception and rotavirus vaccine safety in Canada
Bibliographic record
Abstract
BACKGROUND: Intussusception has been identified as a rare adverse event following rotavirus immunization. We sought to determine the incidence of intussusception among infants in Canada both before and after introduction of rotavirus immunization programs. METHODS: We used Canadian Institute for Health Information (CIHI) Discharge Abstract Database (DAD) to identify infants under 1 y of age who were admitted to a Canadian hospital, which the exception of Quebec, which does not submit data to CIHI, with a diagnosis of intussusception (ICD-10 code K56.1, and ICD-9 code 560) between January 1st, 2003 and December 31, 2013. We compared rates of intussusception hospitalization before and after rotavirus vaccine program introduction. Rates were adjusted for calendar year, age (in months), sex and region using Poisson regression models. Denominator data for infants under 1 year, stratified by age in months, were obtained from Statistics Canada. RESULTS: Annual intussusception hospitalization rates ranged from 20-30 per 100,000 infants over the study period, with no evidence of a trend over time. Intussusception hospitalization rates were highest in infants 4 to <8 months and lowest in those under 2 months or between 10 and <12 months. Males had higher rates than females both overall and within each age group. The rate of intussusception hospitalization after rotavirus vaccine program introduction was 22.4 (95% CI: 18.3, 27.4) compared to 23.4 (95% CI: 21.5, 25.4) per 100,000 before program introduction. CONCLUSIONS: We have described baseline intussusception hospitalization rates for infants in Canada and have found no evidence of a change in rate after implementation of routine rotavirus immunization programs.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 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".