Predictive Factors of Non-Inflammatory Small Bowel Obstruction After Bowel Resection in Crohn’s Patients
Bibliographic record
Abstract
Background: The aim of the study was to investigate the risk factors associated with the development of small bowel obstruction (SBO) in Crohn's disease (CD) after small bowel resection (SBR) that are not due to active/recurrent inflammation. Methods: We conducted a retrospective cohort study of patients who had SBR for active or complicated CD. Abstracted data included demographics, phenotype, therapies for CD, endoscopic disease recurrence, and several surgical variables. The primary outcome was the development of non-inflammatory SBO (NI-SBO) within 5 years after SBR. Results: A total of 335 patients were included. The cumulative rates of NI-SBO at 6 months, 1 year, and 5 years were 5 (1.5%), 8 (2.4%), and 29 (8.9%), respectively. Variables associated with the development of NI-SBO were active macroscopic or microscopic inflammation in the surgical margins (13 (56%) vs. 65 (27%), P = 0.004), open resection (vs. laparoscopic resection) (12 (41.4%) vs. 60 (19.5%), P = 0.0006) and a higher median number of previous resections (2 (interquartile range (IQR) 2 - 3) vs. 1 (IQR 1 - 2), P = 0.0002). Only 21% of patients who developed NI-SBO required surgical intervention. Conclusions: The incidence of NI-SBO after SBR in CD is low and associated with inflammation at the margins of the resected bowel, previous bowel resections, and an open laparotomy approach. Most NI-SBOs resolve with medical management.
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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 | 0.003 |
| 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 | 0.001 | 0.001 |
| 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".