Epidemiological profile of inflammatory bowel disease in Caxias do Sul, Brazil: a cross-sectional study
Bibliographic record
Abstract
BACKGROUND: Inflammatory bowel diseases affect mostly young patients and have a huge impact on their quality of life and growing treatment costs. Currently, there are few Brazilian studies concerning their epidemiological profile. OBJECTIVE: The aim of this study was to describe the regional clinical and epidemiological profile of these pathological conditions in Caxias do Sul, Brazil. DESIGN AND SETTING: Cross-sectional study in Caxias do Sul (RS), Brazil. METHODS: A search for patients was conducted in the municipality’s special medications pharmacy using the International Classification of Diseases, and medical records were manually reviewed for data collec- tion. Sixty-seven patients were included. RESULTS: The patients’ mean age was 46.5 years and females predominated (71.6%). Ulcerative colitis was the most prevalent disease (70%) and Montreal E3 was the most prevalent presentation. The mean age at diagnosis was 39 years. Most patients had recently undergone colonoscopy (67%). Only five patients (7.4%) had records of hospital admission due to the disease, while 12 (18%) underwent a surgical proce- dure during follow-up. Sixty patients (89.5%) were using aminosalicylates, while less than one fifth were using immunosuppressants or immunobiological drugs: 19.4% and 14.9%, respectively. CONCLUSION: The profile of inflammatory bowel disease patients in this region of Brazil is similar in some characteristics to other published Brazilian data, although it differs in others such as higher frequency of pan- colitis. A prospective study on these patients is planned in this region, in order to improve the data quality.
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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 | 0.000 | 0.000 |
| 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".