Seroprevalence of celiac disease in patients with autoimmune hepatitis
Bibliographic record
Abstract
BACKGROUND AND AIMS: Prevalence data of celiac disease (CD) in patients with autoimmune hepatitis (AIH) are scarce. We investigated the relationship between AIH and CD by assessing the prevalence of IgA tissue antitransglutaminase antibodies (TGA) and antiendomysium antibodies (EMA) in a large cohort of AIH patients. METHODS: The frequency of CD was determined by TGA antibody serology in a cohort of 460 AIH patients. In case of TGA positivity, patients were further tested for EMA serology. Retrospective data on previously diagnosed CD and patient characteristics were retrieved from computerized or written medical records. Findings were compared with archival data on the prevalence of CD in the Netherlands (n=1440). RESULTS: Six patients had a known history of CD and were currently in remission as determined by negative TGA serology. In addition, 10 of the 460 AIH patients (2.2%) had positive IgA TGA. Diagnosis of CD was further substantiated by positive EMA antibodies in these patients. Combined, CD was found in 3.5% of AIH patients compared with 0.35% in the general Dutch population (P<0.001). When excluding patients with either a primary biliary cirrhosis or primary sclerosing cholangitis overlap, in 11 (2.8%) AIH patients, CD was found. CONCLUSION: This is the largest serological study on the association between AIH and CD and demonstrates that the presence of CD in AIH patients is more common compared with the general population; yet, it is not as high as described in some previous small studies. The possibility of concurrent CD should be considered in all AIH patients.
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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 | 0.001 |
| 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".