O-004 YI Antibiotics and Risk of New Onset Inflammatory Bowel Disease
Bibliographic record
Abstract
Previous studies have suggested that antibiotics may be associated with new onset inflammatory bowel disease (IBD). The aim of this study was to evaluate antibiotic exposure as a risk factor for developing IBD. A literature search using Medline, Cochrane, and Embase databases as well as major conference abstracts from the last 2 years was performed to identify comparative studies providing data on the association between antibiotic use and newly diagnosed IBD. Included studies reported Crohn’s disease (CD), ulcerative colitis (UC), or a composite of both (IBD) as the primary outcome and evaluated antibiotic exposures prior to diagnosis of IBD. Data on CD, UC, and IBD incidence and antibiotic exposure were extracted from each study. A random-effect meta-analysis was conducted to determine overall pooled estimates and 95% confidence intervals (CI) for the incidence of IBD in patients exposed to antibiotics and those not exposed. A total of 12 observational studies (9 case-control and 3 cohort) that included 8,297 patients diagnosed with IBD were analyzed. The pooled odds ratio (OR) for IBD among patients exposed to any antibiotic was 1.62 (95% CI 1.31–2.01). Antibiotic exposure was significantly associated with CD (OR = 1.85, 95% CI 1.42–2.40) but was not significant for UC (OR = 1.08, 95% CI 0.91–1.27). When combining data from studies that reported on specific classes of antibiotics, all antibiotics appeared to be associated with IBD with the exception of penicillin (OR = 1.12, 95% CI 0.76–1.64). Exposure to metronidazole (OR = 5.01, 95% CI 1.65–15.25) or quinolones (OR = 1.79, 95% CI 1.03–3.12) was most strongly associated with new onset IBD. Exposure to antibiotics appears to increase the odds of being newly diagnosed with IBD. Most antibiotic classes are associated with IBD. Antibiotic use is associated with new onset CD but not new onset UC.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.001 |
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".