Survey of the initial management of celiac disease antibody tests by ordering physicians
Bibliographic record
Abstract
BACKGROUND: Appropriate interpretation of a positive celiac antibody test by an ordering physician is important in order to institute proper management. We evaluated why children with an initial positive celiac serology were not referred for diagnostic biopsy or followed with serial testing by the ordering physician. METHODS: Consecutive celiac serologies in all patients less than 18 years of age were evaluated over 3.5 years and 775 children with a positive tissue transglutaminase antibody (TTG) were identified. If no management of a positive TTG could be identified, a survey was sent to the ordering physician. Responses were categorized as appropriate or inappropriate management. RESULTS: Of the 775 patients with a positive TTG, 193 (24.9%, 95% CI 21.9-28.1%) received no follow-up management. We contacted 173 ordering physicians and 120 (69%) responded. Of the 120 responses, 55 patients (45.8%, 95% CI 36.8-55.1%) were managed appropriately and 46 (38.3%, 95% CI 29.7-47.7%) were considered to be inappropriately managed when no repeat TTG was obtained within 18 months. Reasons for inappropriate management included: screen considered to be false positive (44.7%), patient was not experiencing symptoms of celiac disease (31.6%), symptoms had resolved (15.8%), results were not indicative of celiac disease (26.3%) and patients started a gluten-free diet with no evaluation of response (15.8%). In 19 patients the TTG was not acted upon for technical reasons. CONCLUSIONS: Positive TTGs require appropriate interventions. These include: subspecialist referral for further evaluation and/or repeat testing to evaluate: 1) treatment response or 2) patients with minimal or no symptoms.
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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 | 0.014 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".