Trabeculotomy in the Treatment of Pediatric Uveitic Glaucoma
Bibliographic record
Abstract
PURPOSE: To evaluate the efficacy and safety of trabeculotomy in the treatment of pediatric uveitic glaucoma (UG). MATERIALS AND METHODS: We retrospectively reviewed all cases that underwent trabeculotomy for pediatric UG at our center between 2008 and 2014. Up to 2 trabeculotomies per eye were performed in patients with medically controlled uveitis. Surgical success was defined as final intraocular pressure <22 mm Hg and ≥6 mm Hg after 1 or 2 trabeculotomies, with or without medications. Kaplan-Meier survival analyses were done. RESULTS: A total of 33 trabeculotomies were performed in 28 eyes of 22 patients. Diagnoses included UG associated with juvenile idiopathic arthritis (68.2%), idiopathic uveitis (22.7%), and pars planitis (9.1%). The average age at surgery was 9.8±3.7 (5 to 17) years. With a mean follow-up of 33.6±18.3 (10 to 78) months, the overall surgical success was 81.8%. The cumulative survival probability after up to 2 trabeculotomies was 0.86 (95% confidence interval, 0.71-0.93) at 12 months and 0.77 (95% confidence interval, 0.60-0.87) at 24 months. Four (11.5%) eyes required a second trabeculotomy to achieve surgical success and 4 (7.7%) required filtrating procedures. Intraocular pressure improved from 31.4±7.6 (18 to 50) mm Hg preoperatively to 15.0±3.6 (8 to 23) mm Hg at final visits, whereas the number of glaucoma medications decreased from 4.2±1.1 (1 to 5) to 0.4±1.0 (0 to 4). Visual acuity and intraocular inflammation remained stable (P>0.05) and there were no major complications. CONCLUSIONS: Trabeculotomy is a safe and effective surgery for pediatric UG.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".