A226 THE EFFICACY OF MEDICAL THERAPY TO PREVENT SURGERY AND IMPROVE OUTCOMES AMONG PATIENTS WITH STRICTURING CROHN’S DISEASE: A SYSTEMATIC REVIEW
Bibliographic record
Abstract
Abstract Background Despite the advancements in inflammatory bowel disease (IBD) management, the percentage of Crohn’s Disease (CD) patients presenting with obstructive symptoms due to small and large bowel strictures is estimated to be 25% and 10%, respectively. Treatment of CD has advanced over the past 20 years to include safer, more targeted options that carry less morbidity than surgical intervention. However, the efficacy of medical therapy once fibrosis has begun is theoretically reduced and, until recently, has had limited study. Aims The aim of this systematic review is to examine the efficacy of medical therapies, such as biologics (TNF inhibitors, interleukin inhibitors, anti-integrin therapy) and immunomodulators (thiopurines and methotrexate) to avoid the need for surgical intervention in stricturing Crohn’s disease. Methods We searched Medline, Embase, the Cochrane library, and Web of Science for experimental (i.e., randomized and non-randomized controlled trials), quasi-experimental (i.e., interrupted time series) and observational studies (i.e., cross-sectional surveys) examining the effect of medical therapies among adult and pediatric CD patients admitted for the management of strictures. Records were screened, in duplicate and independently, by their title and abstract and then full-text and relevant data were extracted using a standardized data extraction sheet. Efficacy data were pooled using meta-analyses, when applicable, or synthesized narratively. Results Our preliminary search yielded a total of 1059 unique records and 22 studies (3 RCTs, 19 cohort studies) were included in our analysis. Results from 8 cohort studies show that among 546 patients receiving TNF antagonists, 80% responded to treatment and did not require surgery at an average follow-up period of 4.1 years (95% CI 71% to 88%). Furthermore, one RCT and one cohort study found that Azathioprine in combination with anti-TNF therapy improved obstructive symptoms and reduced the odds of hospitalization and surgery by half. Conclusions Our review highlights systemic medical therapy, namely TNF antagonists, as a promising solution to prevent the need for surgery among patients with stricturing Crohn’s disease. More robust research is needed to confirm these findings and compare their efficacy. Funding Agencies None
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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 | 0.008 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.011 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".