Gonioscopy-assisted transluminal trabeculotomy is an effective surgical treatment for uveitic glaucoma
Bibliographic record
Abstract
BACKGROUND: To assess the efficacy and safety of gonioscopy-assisted transluminal trabeculotomy (GATT) in uveitic glaucoma (UG). METHODS: A retrospective interventional case series in which 33 eyes of 32 patients with UG underwent GATT with or without concomitant cataract extraction and intraocular lens implantation (CE/IOL) at three Canadian treatment centres from October 2015 to 2020. The main outcome measure was surgical success defined as an intraocular pressure (IOP) ≤18 mm Hg and at least one of the following: IOP within one mm Hg of baseline on fewer glaucoma medications as compared with baseline or a 30% IOP reduction from baseline on the same or fewer medications. Secondary outcome measures were IOP, medication usage and surgical complications. RESULTS: Mean patient age (mean±SD) was 49±16 years (range: 18-79) and 44% were female. GATT was performed as a standalone procedure in 52% of cases and the remainder were combined with CE/IOL. Surgical success was achieved in 71.8% (SE: 8.7%) of cases. Mean preoperative IOP (±SD) was 31.4±10.8 mm Hg on a median of 4 medications. 59% of patients were on oral carbonic anhydrase inhibitors (CAIs) prior to surgery. After 1 year, average IOP was 13.8 mm Hg on a median 1 medication, with 6% of patients being on oral CAIs. No sight threatening complications occurred during surgery or follow-up. CONCLUSION: GATT is an effective surgical strategy in the management of UG. This microinvasive conjunctival-sparing procedure should be considered early in these patients.
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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) | 0.001 | 0.001 |
| 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) | 0.001 | 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 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".