Anti-CD20 Treatment of Giant Cell Hepatitis With Autoimmune Hemolytic Anemia
Bibliographic record
Abstract
Giant cell hepatitis with autoimmune hemolytic anemia (GCH-AHA) is a rare autoimmune disease of infancy characterized by severe liver disease associated with Coombs-positive hemolytic anemia. We recently showed that GCH-AHA is probably caused by a humoral immune mechanism. Such data support the use of rituximab, an anti-CD-20 monoclonal antibody specifically targeting B lymphocytes, as a treatment for GCH-AHA. We describe here the detailed clinical evolution of 4 children with GCH-AHA who showed a complete response to rituximab. All patients shared a severe course of the disease with poor control on standard and aggressive immunosuppression. Rituximab was well tolerated, and no side effects or infections were registered. Several doses were needed to induce remission, and 5 to 11 additional maintenance injections were necessary in the 2 more severe cases. Weaning from corticosteroids was achieved in all subjects. A steroid-sparing effect was noted in the 3 children who started rituximab early in the course of the disease. Overall, we show here that there is a strong rationale for treating GCH-AHA with rituximab. Early treatment could reduce the use of corticosteroids. Nevertheless, short-term steroids should be initially associated with rituximab to account for autoantibodies' half-life. Repeated injections are needed to treat and prevent relapses, but the best frequency and duration of treatment remain to be defined.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".