Safety and Outcomes of Bariatric Surgery in Patients With Inflammatory Bowel Disease: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: The need for surgical management of severe obesity in the context of inflammatory bowel disease (IBD) is becoming an increasingly common clinical scenario, yet has been met with significant reservation due to the paucity of current data from which to inform evidence-based clinical decision making. The aim of our study was to perform a systematic review to characterize and evaluate the safety and efficacy of bariatric surgery in IBD patients. Methods: A medical librarian developed and executed comprehensive searches on November 2, 2021. The population of interest was adult subjects (>18 years) diagnosed with inflammatory bowel disease (IBD) undergoing any type of bariatric surgery. Meta-analysis was used to evaluate outcomes using RevMan 5.4.1. Results: A total of 330 687 patients were identified within the 11 studies included. Within all included studies there were 1595 patients with IBD. Patients had a mean weighted age of 46.0, with a female predominance (n = 1287, 80.7%). The mean duration of follow up was 39.7 months. Metabolic and anthropometric outcomes were only reported in noncomparative studies evaluating only patients with IBD, limiting the ability to complete meta-analysis. Meta-analysis revealed that IBD was associated with increased rates of postoperative complications (RR 2.14; 95% CI 1.87-2.44; P < .00001) in comparison to controls without IBD. Conclusion: While bariatric surgery presents an effective weight loss option for patients with IBD, these patients are associated with higher rates of postoperative complications. This work highlights the need to better delineate the effect of bariatric procedures for patients with IBD with respect to both metabolic and IBD-related outcomes.
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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 | 0.015 | 0.038 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.033 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".