Rate and risk factors of postoperative endoscopic recurrence of moderate- to high-risk Crohn's disease patients - A real-world experience from a Middle Eastern cohort
Bibliographic record
Abstract
Background: Crohn's disease (CD) frequently recurs after intestinal resection. Azathioprine (AZA) and biological therapies have shown efficacy in preventing postoperative recurrence (POR). Data on POR from Middle Eastern populations is lacking. This study aimed to evaluate the rate of endoscopic POR in a cohort of CD patients who underwent ileocecal resection (ICR), and to assess the effectiveness of AZA and biological therapies in reducing the risk of disease recurrence. Methods: We performed a retrospective cohort study on 105 CD patients followed at our center, who underwent ileal resection and were at moderate to high risk for POR. Clinical and laboratory data were collected; the primary endpoint was post ICR endoscopic recurrence at 24 months defined by Rutgeerts' score of i2 or more despite treatment. Results: In total, 105 patients with Crohn's disease met our inclusion criteria; 76.2% were in remission and did not have endoscopic POR at 24 months. Further, 41.9% were on biological therapy, and 34.3% were mainly on AZA. Out of the 28.2% who had POR, approximately 15% were on biological therapies. Penetrating phenotype was the only predictive factor for decreasing POR (OR = 0.19, 95% CI: 0.04-0.98, P = 0.04) as identified in multiple logistic regression analysis. Conclusions: The use of biological therapies post-surgery was not superior than AZA in reducing the endoscopic POR for mod- high risk CD patients. Only penetrating behavior of the CD was associated with significantly lower risk of endoscopic recurrence. This finding is worth further investigation in more robust study designs and among larger samples of patients.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".