Intraocular methotrexate for epithelial downgrowth: long-term outcomes in a multicentre case series
Bibliographic record
Abstract
BACKGROUND/AIMS: Sheet-like type of epithelial downgrowth (EDG) is not easily amenable to surgical excision. We describe long-term outcomes in patients with EDG treated with intraocular methotrexate (MTX). METHODS: This is a retrospective, multicentric case series including 10 eyes (nine patients) treated with intraocular MTX for sheet-like EDG. Relevant ocular history, previous EDG treatments, MTX injection regimen, long-term outcomes and complications are reported. RESULTS: All cases were associated with intraocular surgery. Most patients were treated with 400 µm/0.1 mL MTX injections with a starting frequency of two times per week or weekly injections. Mean and SD number of injections per eye was 16±13 injections and duration of follow-up was 54±36 months (range: 7-120 months). Eradication of EDG was achieved in seven eyes of which one required a second MTX treatment course to achieve eradication, while clinical resolution with recurrence was observed in two. One treatment failure occurred despite eight weekly injections which slowed but did not halt EDG progression; the patient later requested that treatments be stopped given difficulty to come to follow-ups. Surface epitheliopathy developed in eight patients and was used to titrate MTX treatment. Six patients also developed endothelial failure. CONCLUSION: We report the largest case series of diffuse, sheet-like EDG treated with intraocular MTX with follow-ups up to 10 years. Intraocular MTX may be used effectively to achieve eradication of EDG in cases where surgery is not amenable. However, further recommendations to guide treatment remain warranted.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".