Normalization Time of Celiac Serology in Children on a Gluten‐free Diet
Bibliographic record
Abstract
OBJECTIVES: Response to a gluten-free diet (GFD) in children with celiac disease is determined by symptom resolution and normalization of serology. We evaluated the rate of normalization of the transglutaminase (TTG) and antiendomysial (EMA) for children on a GFD after diagnosis. METHODS: Celiac serologies were obtained over 3.5 years after starting a GFD in 228 newly diagnosed children with biopsy-proven celiac disease. Patients were classified into categories based on serology (group A, TTG ≥10 × upper limit of normal [ULN] and EMA ≥ 1:80; group B, TTG ≥10 × ULN and EMA ≤ 1:40; and group C, TTG <10 × ULN) and by severity of histologic injury at diagnosis. RESULTS: In children with the highest serology at diagnosis (group A), 79.7% had an abnormal TTG at 12 months after diagnosis (mean TTG 12 months, 68.8 ± 7.3, normal <20 kU/L). At 2 years, an abnormal TTG persisted in 41.7%. In contrast, only 35% of children with the lowest serology at diagnosis (group C) displayed an abnormal TTG at 12 months (mean TTG 14.3 ± 1.9 kU/L). In those with the most severe mucosal injury, Marsh 3C, 74.2% and 33.2% had an abnormal TTG at 1 and 2 years. CONCLUSIONS: Normalization of celiac serology took >1 year in approximately 75% of GFD-compliant children with the highest celiac serology or most severe mucosal injury at diagnosis. Clinicians must consider serology and histology at diagnosis to properly evaluate response to GFD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".