Outcome in pediatric celiac disease is independent of the diagnostic approach in patients with high antibody levels
Bibliographic record
Abstract
OBJECTIVES: European Society for Paediatric Gastroenterology, Hepatology and Nutrition (ESPGHAN) guidelines enable the diagnosis of celiac disease (CD) without biopsies in patients with immunoglobulin A (IgA)-antibodies against tissue transglutaminase (TGA-IgA) ≥ 10× the upper limit of normal (ULN) and positivity of endomysial antibodies in a second blood sample. Limited data exist comparing the biopsy versus the nonbiopsy diagnostic approach regarding long-term outcomes in CD patients. Our study aimed to investigate the influence of the diagnostic approach on adherence to gluten-free diet (GFD), serological remission (defined as normalization of TGA-IgA during follow-up (FU)) and clinical remission in CD patients with TGA-IgA ≥ 10× ULN. METHODS: Retrospective multicenter study. Patients with CD and TGA-IgA ≥ 10× ULN at diagnosis were included in the study. Patients with confirmed diagnosis by biopsy were compared to patients diagnosed by nonbiopsy approach using univariate analysis, Kaplan-Meier survival curve, and logistic regression models. RESULTS: A total of 282 CD patients (192 [68.1%] in the biopsy group; 90 [31.9%] in the nonbiopsy group) were analyzed. The median time to normalization of TGA-IgA was 16.5 months [interquartile range, IQR: 13, 28] in the biopsy and 15 months [IQR: 12, 26] in the nonbiopsy group; p = 0.14). Rates of normalized TGA-IgA at first to third-year FU were comparable between both groups. Adherence to GFD did not seem to be influenced by the diagnostic approach. CONCLUSIONS: The nonbiopsy approach is not inferior to the biopsy approach in terms of adherence to GFD and serological remission in patients with CD.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 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".