Fecal Calprotectin and Clinical Disease Activity in Pediatric Ulcerative Colitis
Bibliographic record
Abstract
Objective. To explore fecal calprotectin levels in pediatric ulcerative colitis (UC) in relation with the validated clinical activity index PUCAI. Methods. This study included all 37 children (median age 14 years) with UC who had calprotectin measured (PhiCal ELISA Test) by the time of PUCAI assessment at the Children's Hospital of Helsinki in a total of 62 visits. Calprotectin values <100 μ g/g of stool were considered as normal. The best cut-off value of each measure to predict 3-month clinical outcome was derived by maximizing sensitivity and specificity. Results. In clinically active disease (PUCAI ≥ 10), calprotectin was elevated in 29/32 patients (91% sensitivity). When in clinical remission, 26% (8/30) of the children had normal calprotectin but 7 (23%) had an exceedingly high level (>1000 μ g/g). The best cut-off value for calprotectin for predicting poor outcome was 800 μ g/g (sensitivity 73%, specificity 72%; area under the ROC curve being 0.71 (95%CI 0.57-0.85)) and for the PUCAI best cut-off values >10 (sensitivity 62%, specificity 64%; area under the ROC curve 0.714 (95%CI 0.58-0.85)). Conclusion. The clinical relevance of somewhat elevated calprotectin during clinical remission in pediatric UC is not known and, until further evidence accumulates, does not indicate therapy escalation.
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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 | 0.004 |
| 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".