Ulcerative colitis in northern Portugal and Galicia in Spain
Bibliographic record
Abstract
BACKGROUND: Clinical and therapeutic patterns of ulcerative colitis (UC) are variable in different world regions. The purpose of this study was to examine two close independent southern European UC populations from 2 bordering countries and observe how demographic and clinical characteristics of patients can influence the severity of UC. METHODS: A cross-sectional study was conducted during a 15-month period (September 2005 to December 2006) based on data of 2 Web registries of UC patients. Patients were stratified according to the Montreal Classification and disease severity was defined by the type of treatment taken. RESULTS: A total of 1549 UC patients were included, 1008 (65%) from northern Portugal and 541 (35%) from Galicia (northwest Spain). A female predominance (57%) was observed in Portuguese patients (P < 0.001). The median age at diagnosis was 35 years and median years of disease was 7. The majority of patients (53%) were treated only with mesalamine, while 15% had taken immunosuppressant drugs, and 3% biologic treatment. Most patients in both groups were not at risk for aggressive therapy. Extensive colitis was a predictive risk factor for immunosuppression in northern Portugal and Galicia (odds ratio [OR] 2.737, 95% confidence interval [CI]: 1.846-4.058; OR 5.799, 95% CI: 3.433-9.795, respectively) and biologic treatment in Galicia (OR 6.329, 95% CI: 2.641-15.166). Younger patients presented a severe course at onset with more frequent use of immunosuppressors in both countries. CONCLUSIONS: In a large population of UC patients from two independent southern European countries, most patients did not require aggressive therapy, but extensive colitis was a clear risk factor for more severe disease
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".