Epithelial downgrowth masquerading as granulomatous anterior and intermediate uveitis with histopathologic evidence of 5-FU treatment
Bibliographic record
Abstract
Purpose: Highlight an unusual case of epithelial downgrowth (EDG) masquerading as granulomatous anterior and intermediate uveitis with histopathologic evidence of 5-fluorouracil (5-FU) treatment. Case description: A 33-year-old man presented after multiple corneal surgeries and neodymium-doped yttrium aluminum garnet (Nd:YAG) capsulotomies with subacute angle closure, pain, light sensitivity, and decreased vision. Exam was notable for granulomatous keratic precipitates, an opacified lens capsule, and vitreous cell/haze. An anterior chamber paracentesis was sent for 16 s (pan-bacterial) and 28 s (pan-fungal) rRNA polymerase chain reaction testing, which returned negative. Diagnostic argon laser photocoagulation was performed on the iris and lens capsule, which blanched upon laser photocoagulation, and subsequent iris biopsy confirmed the presence of epithelial downgrowth (EDG). The patient was treated with multiple injections of 5-FU with repeat biopsy demonstrating both a reduction and apparent resolution in epithelial cell burden after 5-FU. Conclusion: This case demonstrates an unusual presentation of EDG in a young patient with granulomatous anterior and intermediate uveitis, where simple office-based procedures of Argon laser photocoagulation and anterior chamber paracentesis helped aid in diagnosis and management. Histopathological examination in serial specimens demonstrated the effect of 5-FU on EGD. To our knowledge, this case is the first to describe histopathological reduction in epithelial cell burden with sustained resolution.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".