Case Report: Use of Amniotic Membrane for Tectonic Repair of Peripheral Ulcerative Keratitis With Corneal Perforation
Bibliographic record
Abstract
Purpose: To provide a perspective and surgical video demonstration of peripheral corneal ulceration and perforation managed with multilayered amniotic membrane transplantation. Case Reports: Case 1 describes a 48-year-old female with progressive redness and pain, and an inferonasal corneal thinning and perforation in the left eye from peripheral ulcerative keratitis. She underwent conjunctival recession with amniotic membrane inlay and onlay (Sandwich technique) transplantation. The amniotic membrane integrated well, and her Snellen visual acuity improved from 6/21 preoperatively to 6/9 at 3 months post op. Case 2 describes a 78-year-old male with redness and pain with temporal corneal thinning bilaterally and perforation in the right eye from peripheral ulcerative keratitis. Both eyes underwent similar surgical intervention with smooth integration of the amniotic membrane in the cornea and improvement in the visual acuity. Both patients were also started on systemic immunosuppression in collaboration with the rheumatology team. Conclusion: We report successful use of multilayered amniotic membrane transplantation for the treatment of corneal ulceration and perforation. The authors believe the simplicity of the surgical technique, easier access to amniotic membrane tissue, and lower induced post-operative astigmatism all provide advantages over alternative treatment modalities.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.002 |
| 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".