Soluble Blood Markers of Mucosal Healing in Inflammatory Bowel Disease: The Future of Noninvasive Monitoring
Bibliographic record
Abstract
The traditional management of inflammatory bowel disease (IBD) based on symptom control is not considered valid anymore by most specialists in this field, and a new paradigm called "treat to target" has been introduced. This is based on the assessment of disease activity using objective measures. The identification of noninvasive biomarkers is crucial to diagnosis and monitor IBD because frequent endoscopic examinations are costly and uncomfortable for the patient. In this review, we focus on blood markers that may be able to assess mucosal healing (MH) in IBD and recent advances in this area. Introduction of commercial panel to predict MH opens the way for further developments so that colonoscopy or fecal markers may be avoided in some patients. This may also permit frequent monitoring for therapeutic response and achieve MH. It is a challenging area of research to identify a panel of biomarkers that may reflect inflammation and healing to serve as a surrogate of MH.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| 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".