Crohnʼs disease in a southern European country: Montreal classification and clinical activity
Bibliographic record
Abstract
BACKGROUND: Given the heterogeneous nature of Crohn's disease (CD), our aim was to apply the Montreal Classification to a large cohort of Portuguese patients with CD in order to identify potential predictive regarding the need for medical and/or surgical treatment. METHODS: A cross-sectional study was used based on data from an on-line registry of patients with CD. RESULTS: Of the 1692 patients with 5 or more years of disease, 747 (44%) were male and 945 (56%) female. On multivariate analysis the A2 group was an independent risk factor of the need for steroids (odds ratio [OR] 1.6, 95% confidence interval [CI] 1.1-2.3) and the A1 and A2 groups for immunosuppressants (OR 2.2; CI 1.2-3.8; OR 1.4; CI 1.0-2.0, respectively). An L3+L3(4) and L(4) location were risk factors for immunosuppression (OR 1.9; CI 1.5-2.4), whereas an L1 location was significantly associated with the need for abdominal surgery (P < 0.001). After 20 years of disease, less than 10% of patients persisted without steroids, immunosuppression, or surgery. The Montreal Classification allowed us to identify different groups of disease severity: A1 were more immunosuppressed without surgery, most of A2 patients were submitted to surgery, and 52% of L1+L1(4) patients were operated without immunosuppressants. CONCLUSIONS: Stratifying patients according to the Montreal Classification may prove useful in identifying different phenotypes with different therapies and severity. Most of our patients have severe disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".