Prevalence of Celiac Disease in Patients With Primary Biliary Cholangitis: A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
Celiac disease (CeD) has been linked to both autoimmunity and chronic liver disease, but most data on the link to primary biliary cholangitis (PBC) originate from small studies and have yielded conflicting results. A systematic search was performed in the databases of Medline, Embase, Cochrane and Web of Science Core Collection for studies published between 1990 and 2024, using search terms related to CeD, gluten and PBC. The search identified 2016 publications, of which 94 were read in full text. Of these, a total of 25 studies were included in this review, with 22 deemed relevant for meta-analysis. We applied a random effects model to estimate the weighted pooled prevalence along with corresponding 95% confidence intervals (CIs). Results were reported in accordance with the PRISMA guidelines. Our main analysis contained 15 006 individuals with PBC from 22 studies. Among these, 286 (1.9%; 286/15174) had a CeD diagnosis yielding a pooled prevalence of 1.71% (95% CI: 1.08-2.44). When restricting the analysis to 15 studies with biopsy-confirmed CeD, the pooled prevalence was 1.53% (95% CI: 0.51-2.91). This prevalence is comparable to the serology-based prevalence of CeD, of around 1%, in the general population. Our findings suggest that the prevalence of CeD in PBC is similar to that observed in the general population. These findings do not support routine screening for CeD in individuals with PBC.
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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 | 0.014 | 0.028 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.039 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".