Association Between the Use of Antibiotics in the First Year of Life and Pediatric Inflammatory Bowel Disease
Bibliographic record
Abstract
OBJECTIVES: The development of commensal flora in infants has been shown to be sensitive to antibiotic use. Altered intestinal flora is thought to contribute to the etiology of inflammatory bowel disease (IBD), an idiopathic chronic condition. We aimed to determine if early use of antibiotics was associated with the development of IBD in childhood. METHODS: Nested case-control analysis of the population-based University of Manitoba Inflammatory Bowel Disease Epidemiologic Database was carried out. IBD status was determined from a validated administrative database definition. A total of 36 subjects diagnosed between 1996 and 2008 were matched to 360 controls, on the basis of age, sex, and geographic region. Antibiotic data were drawn from the Manitoba Drug Program Information Network, a comprehensive population-based database of all prescription drugs for all Manitobans dating back to 1995. Antibiotic use in the first year of life was compared between IBD cases and controls. RESULTS: The mean age at IBD diagnosis was 8.4 years. Twenty-one cases (58%) had one or more antibiotic dispensations in their first year of life compared with 39% of controls. Crohn's disease was diagnosed in 75% of IBD cases. Those receiving one or more dispensations of antibiotics were at 2.9 times the odds (95% confidence interval: 1.2, 7.0) of being an IBD case. CONCLUSIONS: Subjects diagnosed with IBD in childhood are more likely to have used antibiotics in their first year of life.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.002 | 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".