Meta‐Analysis: Improvement of Bowel Urgency With Advanced Therapies for Inflammatory Bowel Disease
Bibliographic record
Abstract
BACKGROUND: Inflammatory bowel diseases (IBD) are chronic conditions that significantly affect quality of life. Bowel urgency, a particularly disruptive symptom of IBD, is often underreported in clinical trials. AIMS: To examine the effects of IBD therapies on bowel urgency (BU), focusing on the degree and durability of improvement. METHODS: We searched MEDLINE, Embase, and Cochrane databases in December 2024 for studies that reported a BU outcome for IBD therapies. We included only those studies that reported the absence of BU as a quantitative, binary outcome in the meta-analysis. We also performed a subgroup analysis by IBD subtype. We report risk ratios (RR) with 95% confidence intervals (CI). RESULTS: We included 29 randomised controlled trials (RCTs) and 15 post hoc studies of RCTs representing eight therapeutic agents. There was significantly improved likelihood of BU remission across all induction (RR 1.77, CI 1.51-2.08) and maintenance (RR 2.40, CI 1.54-3.73) therapies compared to placebo, and no major differences between anti-interleukin-23 agents (risankizumab, mirikizumab, guselkumab) and a JAK-inhibitor (upadacitinib). CONCLUSIONS: Advanced IBD therapies with different mechanisms of action produce rapid and sustained improvement in BU. The degree of BU improvement was similar among agents. Areas for future research include investigation of BU outcomes with other IBD therapies, exploration of underlying mechanisms of action, and greater standardisation for measuring BU through validated scores.
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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 | 0.019 | 0.033 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.062 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".