Autoimmune hepatitis and immune dysregulation: A case series
Bibliographic record
Abstract
OBJECTIVE: To assess the presence of inborn errors of immunity (IEI) in a pediatric autoimmune hepatitis (AIH) cohort. STUDY DESIGN: This retrospective study included patients aged 0-18 diagnosed with AIH in our center between 1995 and 2023 and followed by the immunology department for a clinical and/or molecular IEI diagnosis. RESULTS: Among our 83 AIH patients, five (6%) displayed signs of associated IEI. Two of those patients had a genetic confirmation of IEI (SP110 and AIRE homozygous mutations). IEI-related signs were recurrent infections (n=3), immune-mediated cytopenia (n=4) or skin disease (n=2) and autoimmune polyendocrinopathy (n=1). The four patients diagnosed with seronegative AIH responded to immunosuppressive therapy, while the AIH type 2 patient underwent emergent liver transplantation for fulminant liver failure at diagnosis. CONCLUSION: Our small case series highlights the need to look for signs of immune dysregulation in AIH patients. Conversely, as AIH can be atypical in IEI, the threshold should be low to perform a diagnostic liver biopsy in IEI patients suffering from chronic cytolysis. We believe that systematic genetic testing and immune phenotyping of AIH patients who display signs of immune dysregulation will be crucial to better understand the close link between AIH and IEI.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.010 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".