Risk and incidence of colorectal stricture progressing to colorectal neoplasia in patients with inflammatory bowel disease: a systematic review and meta-analysis
Bibliographic record
Abstract
This study aims to assess the risk of colorectal stricture progressing to colorectal neoplasia (CRN) in patients with inflammatory bowel disease (IBD). The literature from PubMed, Embase, Web of Science, and Cochrane Library databases was searched from the date of databases' creation to 5 November 2022. The Newcastle-Ottawa Scale was used to evaluate the quality of the included literature. Meta-analysis was conducted using the Stata 15 software and R 4.04 software. Two case-control studies and 12 cohort studies were eventually included. Colorectal stricture in patients with IBD increased the risk of progressing to CRN [odds ratio (OR): 1.52, 95% confidence interval (CI): 1.02-2.29, P = 0.042], but was irrelevant to the risk of progressing to ACRN (OR: 3.56, 95% CI 0.56-22.70, P = 0.180). The risk of CRN were further distinguished in patients with ulcerative colitis (UC) and Crohn's disease (CD) Our findings showed that colorectal stricture may increase the risk of progressing to CRN in patients with UC (OR = 3.53, 95%CI 1.62-7.68, P = 0.001), but was irrelevant to the risk of progressing to CRN in patients with CD (OR = 1.09, 95% CI 0.54-2.21, P = 0.811). In conclusion, colorectal stricture in patients with IBD can be used as a risk factor for predicting CRN but cannot be used as a risk factor for predicting ACRN. Stricture is a risk factor for CRN in patients with UC but not in patients with CD. More prospective, multi-center studies with large samples are expected to confirm our findings.
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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 | 0.010 | 0.024 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.039 |
| 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 | 0.002 |
| 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".