Serologic Reactivity Reflects Clinical Expression of Ulcerative Colitis in Children
Bibliographic record
Abstract
Background: In contrast to pediatric Crohn's disease (CD), little is known in pediatric ulcerative colitis (UC) about the relationship between disease phenotype and serologic reactivity to microbial and other antigens. Aim: The aim of this study was to examine disease phenotype and serology in a well-characterized inception cohort of children newly diagnosed with UC during the PROTECT Study (Predicting Response to Standardized Pediatric Colitis Therapy). Methods: Patients were recruited from 29 participating centers. Demographic, clinical, laboratory, and serologic (pANCA, ASCA IgA/IgG, Anti-CBir1, and Anti-OmpC) data were obtained from children 4-17 years old with UC. Results: Sixty-five percent of the patients had positive serology for pANCA, with 62% less than 12 years old and 66% 12 years old or older. Perinuclear anti-neutrophil cytoplasmic antibodies did not correspond to a specific phenotype though pANCA ≥100, found in 19%, was strongly associated with pancolitis (P = 0.003). Anti-CBir1 was positive in 19% and more common in younger children with 32% less than 12 years old as compared with 14% 12 years old or older (P < 0.001). No association was found in any age group between pANCA and Anti-CBir1. Relative rectal sparing was more common in +CBir1, 16% versus 7% (P = 0.02). Calprotectin was lower in Anti-CBir1+ (Median [IQR] 1495 mcg/g [973-3333] vs 2648 mcg/g [1343-4038]; P = 0.04). Vitamin D 25-OH sufficiency was associated with Anti-CBir1+ (P = 0.0009). Conclusions: The frequency of pANCA in children was consistent with adult observations. High titer pANCA was associated with more extensive disease, supporting the idea that the magnitude of immune reactivity may reflect disease severity. Anti-CBir1+ was more common in younger ages, suggesting host-microbial interactions may differ by patient age.
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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 | 0.000 | 0.002 |
| 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 | 0.001 | 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".