Antibiotics exposure and risk of inflammatory bowel disease: a systematic review
Bibliographic record
Abstract
Aim: The aim of this study was to critically assess all available evidence suggesting an association between antibiotic exposure and new onset of inflammatory bowel disease (IBD). Materials and methods: This systematic review was conducted according to the PRISMA statement and eligible studies were identified through search of PubMed, Embase and the Cochrane Library. Data on patient demographics, antibiotic exposure and confounding factors were analyzed. The Newcastle-Ottawa Scale (NOS) was used to assess the quality of eligible studies. Results: A total of 15 observational studies (10 case control and five cohort) including 8748 patients diagnosed with IBD were systematically reviewed. Antibiotic exposure was mostly associated with Crohn’s disease but not with ulcerative colitis. In particular, penicillin’s, cephalosporins, metronidazole and fluoroquinolones were most commonly associated with the onset of Crohn’s disease. The impact of tetracycline-family antibiotics on the pathogenesis of IBD was not clear. Conclusion: There may be an association between antibiotic exposure and the development of IBD; especially Crohn’s disease. Even though, clinicians should be cautious when prescribing certain antibiotic regimens to patients with a strong family history of IBD, it should be emphasized that available data are not granular enough to reach any definitive conclusions.
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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 | 0.005 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".