Systematic Review: Efficacy, Safety and Metabolic Outcomes of GLP‐1 Receptor Agonists in Inflammatory Bowel Disease
Bibliographic record
Abstract
BACKGROUND: Obesity and metabolic disease are increasingly prevalent in patients with inflammatory bowel disease (IBD) and can influence disease activity and treatment outcomes. Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) are effective for weight loss and metabolic control, yet their safety and effects in IBD remain uncertain as patients with IBD have been excluded from pivotal trials. AIMS: To systematically evaluate the weight-related, metabolic, IBD-specific, and safety outcomes of GLP-1 receptor agonists in adults with IBD. METHODS: We conducted a systematic review according to PRISMA guidelines (PROSPERO CRD42025628850). We searched MEDLINE, Embase, Cochrane Library and ClinicalTrials.gov to 9 September 2025 for studies evaluating GLP-1 RAs in adults with IBD. Primary outcomes were weight-related measures. Secondary outcomes included metabolic parameters, IBD activity, and safety. Risk of bias was assessed using Joanna Briggs Institute (JBI) checklists. RESULTS: We included 14 studies of which 13 were retrospective cohort studies. Ten reported significant reductions in body weight, BMI, or percent weight loss. Four demonstrated improvements in metabolic markers, including decreased haemoglobin A1c and favourable lipid changes. Across multiple datasets, GLP-1 RA use was not associated with increased IBD exacerbations. Several large registries reported reduced risks of corticosteroid use, hospitalisation and surgery among GLP-1 RA users. Adverse events were primarily gastrointestinal, consistent with non-IBD populations. CONCLUSION: GLP-1 RAs appear to be well tolerated in patients with IBD, with observational evidence suggesting potential associations with improved weight, metabolic, and disease-related outcomes. Prospective, IBD-specific studies are required to confirm safety, clarify mechanisms, and define optimal patient selection.
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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 | 0.054 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.010 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".