The Association of Inflammatory Bowel Disease and Eosinophilic Esophagitis: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
BACKGROUND: The association between inflammatory bowel disease (IBD) and eosinophilic esophagitis (EoE) remains unclear. We aimed to perform a systematic review and meta-analysis on the association between EoE, IBD, and other immune-mediated inflammatory diseases. METHODS: A systematic literature search was conducted in Ovid MEDLINE, Ovid Embase, and the Cochrane Central Register of Controlled Trials (Ovid) from inception to July 2023. The primary outcome was to compare the frequency of an EoE diagnosis in IBD and other immune-mediated inflammatory disease processes versus control populations. Where pooled analysis was possible, we reported odds ratios (ORs) with 95% confidence intervals (CIs). I2 values were used to report heterogeneity, with values >50% suggesting substantial heterogeneity. RESULTS: We identified 2612 eligible studies, of which 38 studies were included. A diagnosis of EoE was significantly greater in patients with IBD compared to the general population (OR 3.9; 95% CI, 2.6-5.9 [I2 = 99.5%]). There was no significant increase in EoE in patients with ulcerative colitis compared to Crohn's disease (OR 1.0; 95% CI, 0.7-1.3 [I2 = 88.7%]). EoE was also significantly increased in patients with atopic dermatitis (OR 2.4; 95% CI, 1.9-3.1 3 [I2 = 70.4%]) compared to those without atopic dermatitis. CONCLUSIONS: Both IBD and atopic dermatitis were associated with an increased odds of EoE diagnosis. Further research is needed to determine the underlying mechanisms behind these potential associations.
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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 | 0.016 | 0.032 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.036 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".