Incidence and Prevalence of Inflammatory Bowel Disease in a Northern California Managed Care Organization, 1996-2002
Bibliographic record
Abstract
OBJECTIVE: There are few estimates of the incidence and prevalence of inflammatory bowel disease in North American communities. We sought to estimate the incidence and prevalence of inflammatory bowel disease (IBD), including Crohn's disease (CD), and ulcerative colitis (UC), among 3.2 million members of Kaiser Permanente, Northern California, for the period 1996-2002. METHODS: All health plan members who had one or more diagnoses of CD (ICD-9 code 555) or UC (ICD-9 code 556) on computerized records during the period 1996-2002 and with at least 12 months of membership were identified as possible IBD cases (N = 12,059). We randomly sampled 24% of these for chart review to confirm the diagnosis and obtain the initial diagnosis date. Incidence rates and the point prevalence on December 31, 2002 were standardized to the 2000 U. S. Census. RESULTS: The annual incidence rate per 100,000 persons was 6.3 for CD (95% confidence interval [CI], 5.6-7.0) and 12.0 for UC (CI, 11.0-13.0). The point prevalence per 100,000 on December 31, 2002 was 96.3 for CD (95% CI, 89.6-103.0) and 155.8 for UC (95% CI, 146.6-164.9), increasing to 100.3 and 205.8 per 100,000, respectively, when hospital discharge data from 1985 to 1995 were included. The age-specific incidence of CD was bimodal, while UC incidence rose in early adulthood and remained elevated with advancing age. CONCLUSIONS: The incidence we estimated for CD was similar to the previous U. S. estimate. Our incidence estimate for UC was much higher than the previous U.S. estimate, but similar to that of recent Canadian and European studies. The prevalence we estimated for CD was somewhat lower than previous estimates.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".