Anti‐cyclic citrullinated peptide antibodies in type 1 autoimmune hepatitis
Bibliographic record
Abstract
BACKGROUND: Besides the autoantibodies included in the diagnostic criteria of type 1 autoimmune hepatitis, many other autoantibodies have been described in this condition. Recently, antibodies against cyclic citrullinated peptide have been validated as specific diagnostic and prognostic markers of rheumatoid arthritis. AIM: To assess whether these antibodies are part of the autoantibody repertoire of type 1 autoimmune hepatitis and correlate with rheumatological manifestations. METHODS: Antibodies against cyclic citrullinated peptide were tested by a commercially available enzyme-linked immunosorbent assay. RESULTS: The antibodies were found in 12 of 133 (9%) type 1 autoimmune hepatitis, two of 49 (4%) with primary biliary cirrhosis, one of 80 (1%) with hepatitis C virus-related chronic liver disease and 53 of 89 (60%) with rheumatoid arthritis serum samples. High titres were found only in rheumatoid arthritis and type 1 autoimmune hepatitis. No clinical (in particular rheumatological manifestations), biochemical or immunoserological differences were detectable between antibodies against cyclic citrullinated peptide positive and negative type 1 autoimmune hepatitis sera, with the exception of rheumatoid factor, always negative in the positive ones. CONCLUSIONS: Antibodies against cyclic citrullinated peptide can be detected in a subgroup of patients with type 1 autoimmune hepatitis. They might be part of the wide range of autoantibody production characteristic of this condition and/or, less probably, be predictive of future rheumatoid arthritis development.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| 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".