A60 SIGNIFICANCE OF IBD DIAGNOSIS IN THE BC COLON SCREENING PROGRAM
Bibliographic record
Abstract
Abstract Background There has been evidence of incidental inflammatory bowel disease (IBD) diagnosis in otherwise asymptomatic patients during colonoscopy to follow-up a positive fecal immunochemical test (FIT). Little is known about the significance of subclinical disease and its progression in this population. Aims To determine the incidence and outcome of subclinical IBD in a colon screening program. We hypothesize that the proportion of patients receiving biologic or surgical intervention would be low. Methods IBD cases were identified using the BC Colon Screening Program (BCCSP) database; pilot program at 3 sites from 01/2009–11/2013, and province-wide from 11/2013- 12/2017. Inclusion criteria: diagnosis of IBD at BCCSP colonoscopy performed for positive FIT. Exclusion criteria: prior IBD diagnosis, microscopic colitis. Data obtained through chart review included: demographics, endoscopy and histology reports, and medical/surgical treatment. Results Of 93,994 colonoscopies, 608 were diagnosed with IBD (0.65%) (Figure 1). Chart review of 245 cases at 10 institutions was performed. 65 patients were excluded. Of the 180 cases included, the average age at diagnosis was 59.6 years and 58.9% were male. 70.6% of patients were Caucasian, 12.2% were East Asian, and 7.8% South-east Asian. 49.4% were diagnosed with Crohn’s disease (CD), 33.9% with Ulcerative Colitis (UC), and 16.7% with indeterminate colitis, with a median follow-up of 25.5 months (0–85.9 months). 62.8% of patients received treatment, with 17.8% requiring biologic therapy, and 1.7% requiring surgical intervention. Conclusions This is the largest study assessing subclinical IBD in a colon screening program, with IBD incidence comparable to other publications in this population. However, the high proportion of patients diagnosed with CD is a novel finding. Also, subclinical IBD is not as benign as previously reported as nearly 20% of patients required biologics and/or surgical intervention. Funding Agencies None
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".