Paradoxical Nodular Scleritis during Tocilizumab Therapy: A Case Report
Bibliographic record
Abstract
To the Editor: Ocular manifestations can result from interleukin 6 (IL-6) inhibition, and they should be considered as a possible paradoxical complication when treating inflammatory arthritis. We report the case of a 48-year-old woman with a background history of rheumatoid arthritis (RA), pyoderma gangrenosum, and systemic lupus erythematosus who was diagnosed with anterior nodular scleritis following initiation of tocilizumab (TCZ) therapy. Her RA remained active despite being treated with rituximab (RTX) 2 g intravenously every 6 months, methotrexate (MTX) 20 mg orally every week, sulfasalazine 1 g orally twice daily, hydroxychloroquine 200 mg orally once daily, and folic acid 5 mg orally every week. She was switched to TCZ 8 mg/kg intravenously every 4 weeks. RTX was stopped 5 months prior to TCZ because of primary failure. MTX was discontinued immediately prior to TCZ owing to government funding requirements whereby TCZ can only be given as monotherapy. Following the first dose of TCZ, her RA went into clinical remission, with a 28-joint Disease Activity Score of 2.41 from 6.28 prior. In addition, the inflammatory markers … Address correspondence to Dr. E. Michael, Greenlane Clinical Centre, Department of Ophthalmology, Auckland District Health Board, Auckland, New Zealand. E-mail: EugeneM{at}adhb.govt.nz
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.014 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".