Sarcopenia assessed by computed tomography or magnetic resonance imaging is associated with the loss of response to biologic therapies in adult patients with Crohn's disease
Bibliographic record
Abstract
Sarcopenia occurs in patients with Crohn's disease (CD). However, the association between sarcopenia and loss of response (LOR) to biologic agents remains unclear. This study explored such an association in CD patients. This retrospective study included 94 CD patients who received biologic therapy. The skeletal muscle cross-sectional area at the third lumbar was assessed by computed tomography or magnetic resonance imaging for sarcopenia evaluation. A LOR was defined by fecal calprotectin (FC) < 250 μg/g or >50% reduction from baseline levels or other factors, such as the used agent being replaced by other biologic agents. The association between sarcopenia and LOR was assessed by logistic regression analysis. LOR was observed in 54 patients (57.4%). The prevalence of sarcopenia in the LOR group was higher than that in response group (70.4% vs. 40.0%, p = 0.003). Sarcopenia (odds ratio [OR] = 3.89, 95% confidence interval [CI]: 1.31-11.54), Montreal L1 type (OR = 0.20, 95% CI: 0.06-0.60), perianal lesions (OR = 4.08, 95% CI: 1.31-12.70), and monocytes percentage (OR = 1.27, 95% CI: 1.02-1.57) at baseline were independent associated factors for LOR. Sarcopenia was also associated with LOR in patients who received infliximab (OR = 3.31, 95% CI: 1.11-9.87). Montreal L1 type, perianal lesions, and monocytes percentage (Model 1), and with additional consideration of sarcopenia (Model 2), were developed to predict LOR. Model 2 showed better performance than Model 1 (area under the curve [AUC] 0.82 vs. 0.75). Sarcopenia was associated with the LOR to biological agents or infliximab in adult patients with CD.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".