Body Mass Index Is Associated With Mucosal Disease in Crohn’s: Results of a Case-Control Study
Bibliographic record
Abstract
BACKGROUND: Recent studies have suggested that increased body mass index (BMI) may have an adverse effect on treatment outcomes and natural history in Crohn's disease (CD). We aimed to test the hypothesis that CD patients with higher BMI would be more likely than those with lower BMI to have persistent active mucosal disease. METHODS: We designed a case-control study. Sample population comprised CD patients with active disease at the beginning of observation. At the end of observation, cases had persistent active mucosal disease and controls had entered remission. With multivariable logistic regression models, we evaluated the effect of baseline BMI as a continuous variable and a categorical variable on persistent active mucosal disease. RESULTS: We analyzed data from 104 patients (36 cases and 68 controls). In a model containing BMI as a continuous variable, higher BMI was significantly associated with persistent active mucosal disease (odds ratio (OR) = 1.09 per unit increase; 95% confidence interval (CI), 1.02 - 1.17; P = 0.012). In a model containing BMI as a categorical variable, obese patients were 2.7 times more likely to have persistent active mucosal disease compared to non-obese patients (OR = 2.72; 95% CI, 1.00 - 7.35; P = 0.049). CONCLUSION: Excessive weight measured both quantitatively as BMI and categorically as obesity in CD patients is associated with persistent active mucosal disease.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".