Systematic Review with Meta-analysis: The Impact of Co-occurring Immune-mediated Inflammatory Diseases on the Disease Course of Inflammatory Bowel Diseases
Bibliographic record
Abstract
BACKGROUND AND AIMS: Patients with inflammatory bowel diseases (IBDs) are at risk of developing a variety of other immune-mediated inflammatory diseases (IMIDs). The influence of co-occurring IMIDs on the disease course of IBD remains unknown. The aim of this study was therefore to conduct a systematic review and meta-analysis of the impact of IMIDs on phenotypic presentation and outcome in patients with IBD. METHODS: PubMed and Embase were searched from their earliest records through December 2018 and updated in October 2019 for studies reporting proportions or ratios of IBD-related disease outcomes in patients with and without co-occurring IMIDs. Meta-analyses were performed to estimate summary proportions and risks of the main outcomes. PRISMA guidelines were used, and study quality was assessed according to the Newcastle-Ottawa Scale. RESULTS: A total of 93 studies were identified, comprising 16,064 IBD patients with co-occurring IMIDs and 3,451,414 IBD patients without IMIDs. Patients with IBD and co-occurring IMIDs were at increased risk of having extensive colitis or pancolitis (risk ratio, 1.38; 95% Cl, 1.25-1.52; P < 0.01, I2 = 86%) and receiving IBD-related surgeries (risk ratio, 1.17; 95% Cl, 1.01-1.36; P = 0.03; I2 = 85%) compared with patients without IMIDs. Co-occurrence of IMIDs other than primary sclerosing cholangitis in patients with IBD was associated with an increased risk of receiving immunomodulators (risk ratio, 1.15; 95% Cl, 1.06-1.24; P < 0.01; I2 = 60%) and biologic therapies (risk ratio, 1.19; 95% Cl, 1.08-1.32; P < 0.01; I2 = 53%). CONCLUSION: This meta-analysis found that the presence of co-occurring IMIDs influences the disease course of IBD, including an increased risk of surgery and its phenotypical expression.
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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 | 0.034 | 0.082 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.025 | 0.058 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".