Ultrasound cyclo plasty in advanced glaucoma: Intermediate-term success, predictors for failure and complications
Bibliographic record
Abstract
Purpose To report the intermediate-term success rate of ultrasound cyclo plasty (UCP), predictors for failure and complications in advanced glaucoma. Methods This study included patients with advanced glaucoma who underwent UCP. The main outcome measures were intraocular pressure (IOP), the number of antiglaucoma medications, and the presence of complications. Success was defined as an IOP reduction ≥30% and IOP between 6 mmHg and 18 mmHg with no vision-threatening complications. Cox proportional hazard regression analysis was performed to identify possible predictors for failure. Results We included 65 eyes of 58 patients in the study. The mean IOP and number of antiglaucoma medications decreased significantly from 27.60 ± 5.5 mmHg and 3.40 ± 0.9 at baseline to 17.80 ± 8.0 mmHg (35.51% reduction) and 2.43 ± 1.3 at 12 months and 17.10 ± 8.2 mmHg (38.04% reduction) and 2.41 ± 1.5 at 24 months, respectively ( p < 0.01 for both). The success rates were 66.2% (43/65) and 72.4% (21/29), while the failure rates were 33.8% (22/65) and 27.6% (8/29) at 12 and 24 months postoperatively, respectively. The cumulative probabilities of overall success were 67.7 ± 5.8% and 33.8 ± 5.9% at 12 and 24 months, respectively. High baseline IOP and history of old glaucoma surgery were associated with a higher risk for failure (Hazard ratio = 1.10 and 5.82, p = 0.03 and p < 0.01, respectively). The most common complications were anterior chamber reaction (18.5%) and cataract development/progression (15.4%). Two eyes (3.1%) developed phthisis bulbi. Conclusions Although UCP is effective in lowering IOP in eyes with advanced glaucoma, the intermediate-term success rates were moderate.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".