The Dilemma of Central Serous Retinopathy, a Corticosteroid-induced Complication, in Patients with Ocular Inflammatory Disease
Bibliographic record
Abstract
To the Editor: Rheumatologists sometimes collaborate with ophthalmologists in the management of patients with ocular inflammatory disease. Corticosteroids are often a valuable component of this management. Ophthalmic complications associated with corticosteroid usage include cataract and glaucoma. Corticosteroids have also been implicated in another important cause of visual loss, central serous retinopathy (CSR)1,2, a disorder characterized by neurosensory detachment of the retina affecting the macula. The combination of CSR, best managed by reduction in corticosteroid dosage, and inflammation usually requiring increased corticosteroid dosage creates a dilemma such that worsening visual acuity should be treated paradoxically with reduction in corticosteroid dosage. A 34-year-old male patient with history of juvenile idiopathic arthritis and uveitis complained of blurred vision in the left eye for 3 days, which was 3 weeks after increasing prednisone dose to 10 mg daily. He was functionally blind in the right eye due to band keratopathy. Vision was 20/25+2 in the left eye. The fundus examination revealed CSR, confirmed by ocular coherence tomography (OCT; Figure 1) and fluorescein … Address correspondence to Dr. S.R Gupta, 3375 SW Terwilliger Blvd., Portland, Oregon 97239; E-mail: seema\_r\_gupta{at}yahoo.com
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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 | 0.002 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.015 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 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".