Heterogeneity in pharmacological treatment and outcomes in Crohn’s disease patients in Catalonia: a population-based observational study
Bibliographic record
Abstract
BACKGROUND: Heterogeneity in the treatment of a disease is a marker of suboptimal quality of care. The aim of this study is to evaluate the heterogeneity in the treatment used and the outcomes for Crohn's disease (CD) in Catalonia. METHODS: All patients with CD included in the Catalan Health Surveillance System (data on more than seven million individuals from 2011 to 2017) were identified. The different Catalonian health areas were grouped into 19 district groups (DG). Treatments used rates (systemic corticosteroids, non-biological and biological immunosuppressant) and outcomes rates (hospitalization and surgery) were calculated. RESULTS: The use of systemic corticosteroids presented a decreasing trend over the study period, with an average rate of use in the different territories between 11% and 17%. The use of non-biological immunosuppressant treatment has remained stable, with an average rate of use ranging from 22% to 40% per year depending on the DG. The use of biological immunosuppressant treatment increased with an average rate of use in the different territories ranging from 10 to 23%.Hospitalizations for any reason showed an increasing trend between 2011 and 2017 with an average rate of between 23% and 32% per year depending on the area. Hospitalizations for CD presented a decreasing trend, with an average rate of between 5% and 11% per year. Surgical treatment remained stable over time, rates per year were between 0.5% and 2%. CONCLUSION: A remarkable geographical heterogeneity in the use of different treatments and in outcomes of CD was observed between different geographical areas of Catalonia. KEY MESSAGEThere is a notable geographical heterogeneity in the administration of biological and immunosuppressive treatments to Crohn's disease patients in Catalonia.There is also a geographical heterogeneity in their rates of hospitalization and surgical intervention.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".