Decreasing incidence of inflammatory bowel disease in Eastern Canada: a population database study
Bibliographic record
Abstract
BACKGROUND: Nova Scotia has one of the highest incidences of inflammatory bowel disease (IBD) in the world. We wished to determine trends of IBD over time. METHODS: All Provincial residents have government provided health insurance and all interactions with the hospital, and physician billing systems, are captured on an administrative database. We used a validated measure to define incident cases of Crohn's (CD), ulcerative colitis (UC) and undifferentiated IBD (IBDU). Incidence rates of these diseases for the years 1996-2009 were calculated. RESULTS: Over the study period, 7,153 new cases of IBD were observed of which 3,046 cases were categorized as CD (42.6%), 2,960 as UC (41.4%) and 1,147 as IBDU (16.0%). Annual age standardized incidence rates were very high but have declined for CD from 27.4 to 17.7/100,000 population and for UC from 21.4 to 16.7/100,000. The decline was seen in all age groups and both genders. The decrease was not explained by a small increase in IBDU. CONCLUSION: The incidence of CD and UC are decreasing in Nova Scotia. If replicated elsewhere this indicates a reversal after a long period of increasing occurrence of IBD. This has implications for both epidemiology and health planning.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.008 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".