Can we predict mucosal remission in ulcerative colitis more precisely with a redefined cutoff level of C‐reactive protein?
Bibliographic record
Abstract
AIM: Most patients with ulcerative colitis (UC) with active mucosal disease have a lower C-reactive protein (CRP) level than the classic accepted cutoff level (≤5 mg/l). We aimed to predict the mucosal remission in UC with an optimal cutoff level of CRP when mucosal activity and extensiveness of UC were both considered. METHOD: In this retrospective study, we evaluated CRP values and their relation to mucosal extension and UC activity in 331 colonoscopic examinations performed between December 2016 and March 2019. Endoscopic activity and disease extension were assessed using Mayo scores and the Montreal classification. RESULTS: The Mayo 2 and 3 groups' CRP values were significantly higher when compared with Mayo 0-1 between values of E1 and both E2 and E3 with an increasing trend. The standard CRP cutoff level ≤5 mg/l only yielded 55% specificity in predicting mucosal remission. In the ROC analysis, a CRP cutoff level ≤2.9 mg/l predicted an overall mucosal remission (Mayo 0-1) with 77% sensitivity and 80% specificity, and ≤1.9 mg/l predicted Mayo-0 with 70% sensitivity and specificity. In the clinical remission subgroup, the overall CRP cutoff level was even lower, at ≤1.58 mg/l. CONCLUSION: An overall CRP cutoff level ≤2.9 mg/l predicts mucosal remission in UC better than the standard cutoff ≤5 mg/l. Mucosal remission in stable clinical remission may present with an even lower CRP level. An increasing trend in the CRP level from E1 through E3 even in mucosal remission suggests that both histological inflammation and extensiveness may have some influence on a CRP-based prediction of endoscopic remission.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".