High Doses of Infliximab in the Management of Juvenile Idiopathic Arthritis
Bibliographic record
Abstract
OBJECTIVE: To review our experiences with high-dose infliximab (IFX) to treat juvenile idiopathic arthritis (JIA). We routinely use high doses of IFX (10-20 mg/kg) in children with recalcitrant or highly active JIA. Although biologics have revolutionized treatment of JIA, many patients have active disease despite therapy. Studies have shown benefits of high-dose IFX in several conditions, including inflammatory bowel disease, psoriasis, and idiopathic uveitis. The safety and effectiveness of high-dose IFX have not been evaluated in JIA. METHODS: We performed a retrospective review of children with JIA who received IFX ≥ 10 mg/kg. We recorded all serious adverse events (SAE), medically important infections, and infusion reactions. We also recorded the physician global assessment of disease activity (MD global) and active joint count (AJC) at initiation of high-dose IFX and 3, 6, and 12 months thereafter. RESULTS: Fifty-eight subjects received a total of 1064 infusions over 95 person-years. There were a total of 9 SAE (9.5/100 person-yrs), 7 of which were potentially related to therapy, and 6 infusion reactions (0.5%), none constituting anaphylaxis. Statistically significant improvements were observed in the AJC (median 0, range 0-31, vs 2, 0-39) and MD global (12, 2-31, vs 22, 5-80) over the first year. CONCLUSION: High-dose IFX appears safe in the management of JIA. Future prospective controlled studies are necessary to evaluate its safety and efficacy.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".