Prevalence of stricturing, penetrating complications and extraintestinal manifestations in inflammatory bowel disease detected on cross‐sectional imaging in a tertiary care setting
Bibliographic record
Abstract
BACKGROUND: Stricturing, penetrating complications and extraintestinal manifestations (EIMs) are frequent in patients with inflammatory bowel disease (IBD). There is limited data on the prevalence of these complications in patients with IBD. Therefore, we aimed to assess the burden of these complications detected incidentally on cross-sectional imaging. METHODS: A retrospective study conducted at two tertiary care centers in London, Ontario. Patients (≥18 years) with a confirmed diagnosis of IBD who underwent CT enterography (CTE) or MR enterography (MRE) between 1 Jan 2010 and 31 Dec 2018 were included. Categorical variables were reported as proportions and the mean and standard deviations were reported for continuous variables. RESULTS: A total of 615 imaging tests (MRE: 67.3% [414/615]) were performed in 557 IBD patients (CD: 91.4% [509/557], UC: 8.6% [48/557]). 38.2% (213/557) of patients were male, with mean age of 45.6 years (±15.8), and median disease duration of 11.0 years (±12.5). Among patients with CD, 33.2% (169/509) had strictures, with 7.8% having two or more strictures and 66.3% considered inflammatory. A fistula was reported in 10.6% (54/509), the most common being perianal fistula (27.8% [15/54]), followed by enterocutaneous fistula (16.8% [9/54]), and enteroenteric fistula (16.8% [9/54]). Additionally, 7.4% (41/557) of patients with IBD were found to have an EIM on cross-sectional imaging, with the most prevalent EIM being cholelithiasis (63.4% [26/41]), followed by sacroiliitis (24.4% [10/41]), primary sclerosing cholangitis (4.8% [2/41]) and nephrolithiasis (4.8% [2/41]). CONCLUSIONS: Approximately 40% of patients with CD undergoing cross-sectional imaging had evidence of a stricture or fistulizing disease, with 7% of patients with IBD having a detectable EIM. These results highlight the burden of disease and the need for specific therapies for these disease phenotypes.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
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 | 0.001 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".