Increased Epithelial Gaps in the Small Intestine Are Predictive of Hospitalization and Surgery in Patients With Inflammatory Bowel Disease
Bibliographic record
Abstract
OBJECTIVES: Epithelial gaps resulting from intestinal cell extrusions can be visualized with confocal laser endomicroscopy (CLE) during colonoscopy and increased in normal-appearing terminal ileum of inflammatory bowel disease (IBD) patients. Cell-shedding events on CLE were found to be predictive of disease relapse. The aim of this study was to assess the prognostic value of epithelial gap densities for major clinical events (hospitalization or surgery) in follow-up. METHODS: We prospectively followed IBD patients undergoing colonoscopy with probe-based CLE (pCLE) for clinical events including symptom flares, medication changes, hospitalization, or surgery. Survival analysis methods were used to compare event times for the composite outcome of hospitalization or surgery using log-rank tests and Cox proportional hazards models. We also examined the relationship of gap density with IBD flares, need for anti-tumor necrosis factor therapy, disease duration, gender and endoscopic disease severity, and location. RESULTS: A total of 21 Crohn's disease and 20 ulcerative colitis patients with a median follow-up of 14 (11-31) months were studied. Patients with elevated gap density were at significantly higher risk for hospitalization or surgery (log-rank test P=0.02). Gap density was a significant predictor for risk of major events, with a hazard ratio of 1.10 (95% confidence interval=1.01, 1.20) associated with each increase of 1% in gap density. Gap density was also correlated with IBD disease duration (Spearman's correlation coefficient rho=0.44, P=0.004), and was higher in male patients (9.0 vs. 3.6 gaps per 100 cells, P=0.038). CONCLUSIONS: Increased epithelial gaps in the small intestine as determined by pCLE are a predictor for future hospitalization or surgery in IBD patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".