Fecal Calprotectin Correlates With Disease Extent but Remains a Reliable Marker of Mucosal Healing in Ulcerative Colitis
Bibliographic record
Abstract
INTRODUCTION: Fecal calprotectin (FC) is a marker of mucosal inflammatory activity in ulcerative colitis (UC). FC levels may also be influenced by the extent of disease. We aimed to examine the relationships between FC, mucosal activity, and disease extent and to assess how disease extent affects the diagnostic accuracy of FC. METHODS: We conducted a single-center observational study of patients with UC. Mucosal inflammatory activity was rated by the Mayo Endoscopic Score (MES) and Nancy Histological Index (NHI). The endoscopic and histological extents of disease were categorized by the Montreal classification and colorectal distribution of histologically active inflammation (NHI ≥ 2), respectively. FC was measured by EliA Calprotectin Enzyme fluoroimmunoassay (Phadia). RESULTS: A total of 518 visits by 254 patients were analyzed. In endoscopically active UC (MES ≥ 2), FC levels were significantly lower in proctitis (440 [interquartile range (IQR) 175-1,350] mg/kg) as compared with left-sided colitis (840 [IQR 298-2,011] mg/kg, P = 0.048) or pancolitis (1,690 [IQR 723-2,582] mg/kg, P = 0.00005). In MES ≤1, FC levels were significantly higher in pancolitis (85 [IQR 43-350] mg/kg) as compared with proctitis (24 [IQR 15-116] mg/kg, P = 0.00032) or left-sided colitis (40 [IQR 15-160] mg/kg, P = 0.012). However, FC remained a reliable marker of mucosal healing across all disease extents, with area under the receiver-operating characteristic curve ranging from 0.878 to 0.915, and no significant differences between the extent categories (DeLong test, P ≥ 0.2919). DISCUSSION: FC showed a significant association with disease extent yet remained a reliable surrogate marker for mucosal healing across all disease extents.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".