The Burden of Large and Small Duct Primary Sclerosing Cholangitis in Adults and Children: A Population-Based Analysis
Bibliographic record
Abstract
OBJECTIVES: The epidemiology of primary sclerosing cholangitis (PSC) has been incompletely assessed by population-based studies. We therefore conducted a population-based study to determine: (a) incidence rates of large and small duct PSC in adults and children, (b) the risk of inflammatory bowel disease on developing PSC, and (c) patterns of clinical presentation with the advent of magnetic resonance cholangiopancreatography (MRCP). METHODS: All residents of the Calgary Health Region diagnosed with PSC between 2000 and 2005 were identified by medical records, endoscopic, diagnostic imaging, and pathology databases. Demographic and clinical information were obtained. Incidence rates were determined and risks associated with PSC were reported as rate ratios (RR) with 95% confidence intervals (CI). RESULTS: Forty-nine PSC patients were identified for an age- and gender-adjusted annual incidence rate of 0.92 cases per 100,000 person-years. The incidence of small duct PSC was 0.15/100,000. In children the incidence rate was 0.23/100,000 compared with 1.11/100,000 in adults. PSC risk was similar in Crohn's disease (CD; RR 220.0, 95% CI 132.4-343.7) and ulcerative colitis (UC; RR 212.4, 95% CI 116.1-356.5). Autoimmune hepatitis overlap was noted in 10% of cases. MRCP diagnosed large duct PSC in one-third of cases. Delay in diagnosis was common (median 8.4 months). A minority had complications at diagnosis: cholangitis (6.1%), pancreatitis (4.1%), and cirrhosis (4.1%). CONCLUSIONS: Pediatric cases and small duct PSC are less common than adult large duct PSC. Surprisingly, the risk of developing PSC in UC and CD was similar. Autoimmune hepatitis overlap was noted in a significant minority of cases.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".