Trends in the epidemiology of inflammatory bowel disease in Colombia by demographics and region using a nationally representative claims database and characterization of inflammatory bowel disease phenotype in a case series of Colombian patients
Bibliographic record
Abstract
ABSTRACT: The incidence of inflammatory bowel disease (IBD) is on the rise in Latin America. The aims of this study were to examine epidemiologic trends of IBD in Colombia by demographics, region, urbanicity, and to describe the IBD phenotype in a large well-characterized Colombian cohort.We used a national database of 33 million adults encompassing 97.6% of the Colombian population in order to obtain epidemiologic trends of IBD using International Classification of Diseases 10codes for adults with ulcerative colitis (UC) and Crohn disease (CD). We calculated the incidence and prevalence of UC and CD from 2010-2017 and examined epidemiologic trends by urbanicity, demographics, and region. We then examined the IBD phenotype (using Montreal Classification), prevalence of IBD-related surgeries, and types of IBD-medications prescribed to adult patients attending a regional IBD clinic in Medellin, Colombia between 2001 and 2017.The incidence of UC increased from 5.59/100,000 in 2010 to 6.3/100,000 in 2017 (relative risk [RR] 1.12, confidence interval (CI) (1.09-1.18), P < .0001). While CD incidence did not increase, the prevalence increased within this period. The Andes region had the highest incidence of IBD (5.56/100,000 in 2017). IBD was seen less in rural regions in Colombia (RR=.95, CI (0.92-0.97), p < .01). An increased risk of IBD was present in women, even after adjusting for age and diagnosis year (RR 1.06 (1.02-1.08), P = .0003). The highest IBD risk occurred in patients 40 to 59 years of age. In the clinic cohort, there were 649 IBD patients: 73.7% UC and 24.5% CD. Mean age of diagnosis in CD was 41.0 years and 39.9 years in UC. UC patients developed mostly pancolitis (43%). CD patients developed mostly ileocolonic disease and greater than a third of patients had an inflammatory, non-fistulizing phenotype (37.7%). A total of 16.7% of CD patients had perianal disease. CD patients received more biologics than UC patients (odds ratio: 3.20, 95% CI 2.19-4.69 P < .001).Using both a national representative sample and a regional clinic cohort, we find that UC is more common in Colombia and is on the rise in urban regions; especially occurring in an older age cohort when compared to Western countries. Future studies are warranted to understand evolving environmental factors explaining this rise.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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, unvalidatedMachine predicted; a candidate call from one teacher head, 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".