Long-term Results of Ahmed Valve Implantation With Mitomycin-C in Pediatric Glaucoma
Bibliographic record
Abstract
PRECIS: Mitomycin was used with Ahmed valve implantation in 81 eyes of 63 children. After 5 years, probability of intraocular pressure (IOP) control without glaucoma medication was 35±6%; 57% achieved IOP control with topical medications after 10 years. PURPOSE: The purpose of this study was to determine the long-term outcomes of Ahmed glaucoma valve (AGV) implantation with intraoperative application of mitomycin-C (MMC) for the treatment of childhood glaucoma. METHODS: Retrospective review of children undergoing AGV implantation with subtenon application of MMC between 2000 and 2019. We defined surgical success as a final IOP of 5 to 21 mm Hg with no glaucoma medication, no subsequent glaucoma surgery, and no severe complication. Qualified success was defined if the above criteria were met with topical antiglaucoma medication. RESULTS: Eighty-one eyes of 63 patients were included. The probability of complete success was 72±5% (63% to 83%) at 1 year, 58±6% (48% to 70%) at 2 years, and 35±6% (25% to 48%) at 5 years. The probability of qualified success was 92±3% (87% to 98%) at 1 year, 79±5% (70% to 89%) at 5 years, 57±7% (44% to 73%) at 10 years, and 39±9% (24% to 62%) at 14 years. The IOP was reduced by an average of 10.7±9 mm Hg from preoperative visit to the last follow-up, and the number of medications decreased from 3.0±1.4 to 1.5±1.4 after implantation. CONCLUSIONS: A significant proportion of patients achieved long-term IOP control without glaucoma medication. The majority achieved IOP control with additional topical antiglaucoma medications. When compared with existing AGV implantation in childhood literature, the use of MMC appears to lengthen the drop-free (complete success) duration, as well as the long-term IOP control with topical medications.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".