The application of Montreal classification in different clinical and serological IBD subtypes.
Bibliographic record
Abstract
BACKGROUND/AIMS: Inflammatory bowel disease (IBD) represents the heterogeneous group of disorders with a wide variety of clinical manifestations. The Montreal classification has been developed recently and its accuracy in categorizing of IBD phenotypes needs to be investigated. The aim of the study was to assess the usefulness of the Montreal classification compared to CAI and CDAI in various disease activity, serological and clinical manifestations of IBD. METHODOLOGY: The study was performed in 125 IBD patients: 71 patients with ulcerative colitis, 31 with Crohn's disease and 23 with IBD unclassified (indeterminate colitis). Disease activity and clinical course were assessed using Montreal classification, Clinical Activity Index and Crohn's Disease Activity Index. pANCA and ASCA were measured with ELISA, using widely used, commercial antibody panel (Cogent Diagnostics and Genesis Diagnostics and MedTek kits). RESULTS: No significant correlation has been found between pANCA/ASCA presence and disease activity using CAI and CDAI. ASCA and pANCA-/ASCA+ antibodies pattern had been detected more often in patients with Crohn's disease after surgery, with localization in small or small and large intestine, without perianal lesions and with early disease onset. CONCLUSIONS: Correlations between serotype and certain clinical phenotype are present, which could potentially be of value in the classification of patients particular treatment regimen. We have noticed that clinical course assessment using Montreal classification shows precisely real CD patients state.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".