Hepatic Manifestations in Systemic Juvenile Idiopathic Arthritis and Macrophage Activation Syndrome
Bibliographic record
Abstract
OBJECTIVE: Systemic juvenile idiopathic arthritis (sJIA) is a chronic inflammatory disease characterized by systemic features and arthritis. Macrophage activation syndrome (MAS) is a severe complication of sJIA often involving the liver. MAS confined predominantly to the liver, causing severe hepatitis, has been increasingly recognized. When liver MAS is the primary manifestation, significant hepatic injury can occur; therefore, differentiation from other forms of sJIA-related liver involvement, which may warrant distinct treatment approaches, is required. This study examined liver pathology in patients with sJIA-MAS and explored potential mechanisms. METHODS: This retrospective case series analyzed data from 4 patients with sJIA-MAS who presented with liver dysfunction and underwent core liver biopsies at Cincinnati Children's Hospital Medical Center (2019-2024). RESULTS: Four patients (age range 4-15 years) had elevated transaminases, with 1 meeting MAS criteria and 3 diagnosed with subclinical MAS. Liver biopsies showed portal and sinusoidal inflammatory infiltrates of CD3+ CD8+ T cells and CD163+ macrophages, with extensive hepatocellular damage, including centrilobular parenchymal collapse, multifocal necrosis, and lymphocyte-mediated bile duct injury. One case revealed features of venoocclusive disease, a novel finding. Elevated serum chemokine (C-X-C motif) ligand 9 (CXCL9) and rapid response to emapalumab (anti-interferon γ [anti-IFN-γ]) in all patients suggested IFN-γ-driven liver pathology. CONCLUSION: This study underscores the critical roles of CD8+ T cells, macrophages, and IFN-γ in sJIA-MAS hepatitis. Future research should explore whether serum biomarkers of IFN-γ activity can differentiate sJIA-MAS from other liver pathologies, such as drug-induced liver injury (methotrexate- or anakinra-induced) and hepatic steatosis, to guide tailored therapies.
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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 | 0.000 |
| 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) | 0.002 | 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".