Co-occurrence of Asthma and the Inflammatory Bowel Diseases: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
Background: Inflammatory bowel diseases (IBD) and asthma share genetic and environmental risk factors. Consequently, several observational studies have explored an association between IBD and asthma. We systematically reviewed and summarized the literature on the co-occurrence of asthma and IBD. Methods: MEDLINE and EMBASE (to April 2017) were searched to identify observational studies on the association between asthma and IBD. Relative risks (RR) were pooled using random effects models. Heterogeneity was assessed using the I2 and Cochran Q statistics. Meta-regression based on study design, source of patients (population-based vs. tertiary-care center) and study location was conducted to explain between-study heterogeneity. Results: Eighteen studies were identified (15 Crohn's disease, 15 ulcerative colitis (UC)). Asthma was associated with both Crohn's disease (pooled RR 1.30, 95% confidence interval (CI) 1.16–1.47, I2 = 88%) and UC (RR 1.34, 95% CI 1.24–1.44, I2 = 93%). The study design and source of patients and study location explained between-study heterogeneity in Crohn's disease, but not UC. Conclusion: Asthma is associated with both Crohn's disease and UC. Additional research is needed to determine if one disease influences the risk of developing the other or if the frequent co-occurrence of these diseases result from shared genetic, environmental, and microbial risk factors.
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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 | 0.012 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.035 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 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".