Repair of Eroded Glaucoma Drainage Devices
Bibliographic record
Abstract
PURPOSE: Glaucoma drainage devices (GDD) are used in the surgical management of medically refractory glaucoma. One late serious complication is erosion and exposure of the tube, clip, or plate. In this study, we evaluated the effectiveness of oral buccal mucous membrane allografts with corneal lamellar grafts for the repair of GDD erosions. METHODS: Retrospective consecutive observational case series. All patients who underwent buccal membrane transplants with corneal allografts for the repair of GDD erosions between 2006 and 2010 were included in this study. Primary outcomes were categorized as: (a) success: coverage of the GDD without further repair; (b) qualified success: minor perioperative complications or additional procedures required to maintain success; or (c) failure: GDD reerosion requiring surgery. RESULTS: Nineteen eyes from 17 patients with 20 GDDs were reviewed, of which there were 19 Ahmed valves and 1 Molteno implant. There were 16 cases of tube erosion, 2 cases of plate erosion, and 2 cases of pars plana clip erosion. The mean (SD) number of ocular surgeries before the buccal membrane transplant was 4.8 (2.9). The mean (SD) time to exposure from the original GDD procedure was 4.6 (3.7) years. Analysis of tube erosions alone showed a success rate of 94% after ≥ 1 buccal membrane repairs. Buccal membrane repairs in total were considered a surgical success in 85% of cases with a mean (SD) follow-up of 1.7 (1.2) years. CONCLUSIONS: Buccal membrane transplants are particularly useful in cases of tube erosion.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".