Retroperitoneal Fibrosis During Etanercept Therapy for Rheumatoid Arthritis
Bibliographic record
Abstract
To the Editor: Retroperitoneal fibrosis (RPF) is a rare disease characterized by fibroinflammatory tissue surrounding the abdominal aorta and frequently encasing the ureter1. Empirical therapy includes high doses of corticosteroids as first-line treatment, and in some refractory cases immunosuppressive agents such as azathioprine, mycophenolate mofetil, or tamoxifen1. However, some patients fail to respond to immunosuppressive treatment. New drugs are needed for this patient subset. Catanoso, et al reported the case of a woman with idiopathic RPF whose condition improved after receiving infliximab, a monoclonal antibody directed against tumor necrosis factor-α (TNF-α)2. In contrast, we describe the cases of 2 patients who developed RPF while receiving etanercept, a soluble receptor, another TNF-α blocker for RA. In the Rheumatology Department of Clermont-Ferrand Teaching Hospital, 2 patients with rheumatoid arthritis (RA) developed RPF while receiving TNF-α blockers for RA. A 57-year-old man was effectively treated with etanercept 50 mg/week for seronegative RA for 4 years. He was also treated with perindopril for arterial hypertension and rosuvastatin and aspirin for lower limb arterial disease. He presented with acute lower back pain with fever in 2004. Inflammatory markers were slightly elevated: erythrocyte sedimentation rate (ESR) 31 mm/h, upper limit … Address correspondence to Dr. M. Couderc, Rheumatology Department, Clermont-Ferrand Teaching Hospital, Place Henri Dunant, 63000 Clermont-Ferrand, France. E-mail: mcouderc{at}chu-clermontferrand.fr
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".