The Safety and Efficacy of Noncorticosteroid Triple Immunosuppressive Therapy in the Treatment of Refractory Chronic Noninfectious Uveitis in Childhood
Bibliographic record
Abstract
OBJECTIVE: To assess the safety and efficacy of noncorticosteroid triple immunosuppressive therapy in the treatment of refractory chronic noninfectious childhood uveitis. METHODS: Subjects were retrospectively selected from a database. Patients were included if they were diagnosed with chronic, noninfectious uveitis at 16 years of age or under and treated with triple immunosuppressive therapy for at least 6 months (following failure of a combination of 2 immunosuppressants). Patient demographics, diagnoses, duration of uveitis, drug dosages, active joint inflammation, and ophthalmologic data were recorded. Efficacy outcomes for triple therapy were recorded at 6 months. RESULTS: Thirteen patients with bilateral uveitis were included. Using Standardized Uveitis Nomenclature (SUN) criteria, at 6 months only 11 eyes (42%) had a 2-step improvement in anterior chamber cell inflammation (n = 26). In addition, 2 patients required additional oral corticosteroid treatment. There were 4 significant infectious adverse events during a total of 21.9 patient-years (PY) on triple therapy (0.18 events per PY). CONCLUSION: In this group of children with refractory uveitis, addition of a third immunosuppressive agent did not confer substantial benefit in redressing ocular inflammation and was associated with significant infections in a minority of patients.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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".