A novel location classification system for Crohn’s disease based on small bowel involvement: a better predictor of disease progression
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Bibliographic record
Abstract
Abstract Background Small bowel involvement is related to poor prognosis in Crohn’s disease (CD), which may be a potential marker to stratify patients with a high risk of progression. This study aimed to establish a novel location classification system for CD and to develop a predictive model for disease progression. Methods Consecutive patients with non-stricturing/non-penetrating CD were retrospectively included in the Sixth Affiliated Hospital, Sun Yat-sen University (Guangzhou, P. R. China) between January 2012 and January 2018. Patients were classified into two groups according to disease location: small bowel involvement group and isolated colon group. The primary outcome was disease progression to stricturing or penetrating phenotypes. Progression-free survival was estimated using Cox proportional hazards regression analysis and Kaplan–Meier method. Results A total of 463 patients were analysed, with a median follow-up time of 55.3 months. Patients with small bowel involvement had a higher risk of disease progression than those with isolated colon disease (hazard ratio = 1.998, P = 0.007), while no differences were found between Montreal location classification and disease progression. Median progression-free survival was higher in the isolated colon group than in the small bowel involvement group (84.5 vs 77.3 months, P = 0.006). Four independent factors associated with disease progression were identified: small bowel involvement, duration of onset of >1 year, deep mucosal ulcer, and C-reactive protein levels of ≥10 mg/L (all P < 0.05). The nomogram model based on these factors showed good performance in predicting disease progression, with a C-index of 0.746 (95% confidence interval, 0.707–0.785). Conclusions Classifying CD based on small bowel involvement and isolated colon was superior to the Montreal location classification for predicting disease progression.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 it