Using multiple trabecular micro-bypass stents in cataract patients to treat open-angle glaucoma
Bibliographic record
Abstract
PURPOSE: To evaluate the efficacy of multiple trabecular micro-bypass stents combined with cataract surgery in patients with open-angle glaucoma (OAG) and cataract. SETTING: Private practice, Mississauga, Ontario, Canada. DESIGN: Comparative case series. METHODS: Eyes with OAG had implantation of 2 or 3 micro-bypass stents with concurrent cataract surgery and follow-up through 1 year. Efficacy measures were intraocular pressure (IOP) and topical ocular hypotensive medication use. Safety assessment included complications and corrected distance visual acuity (CDVA). RESULTS: The study comprised 53 eyes (47 patients); 28 had implantation of 2 stents and 25 had implantation of 3 stents. The overall mean 1-year postoperative IOP was 14.3 mm Hg, which was significantly lower than preoperative IOP overall and in each group (P<.001). The target IOP was achieved in a significantly higher proportion of eyes at 1 year versus preoperatively (77% versus 43%; P<.001). Overall, 83% of eyes had a decrease in topical ocular hypotensive medication at 1 year from preoperatively, with a 74% decrease in the mean number of medications (from 2.7 to 0.7) at 1 year (P<.001). The 3-stent group was on significantly fewer medications than the 2-stent group at 1 year (0.4 versus 1.0; P=.04). CONCLUSIONS: Using multiple micro-bypass stents with concurrent cataract surgery led to a mean postoperative IOP of less than 15 mm Hg and allowed patients to achieve target pressure control with significantly fewer medications through 1 year. FINANCIAL DISCLOSURE: Dr. Ahmed is a consultant to Glaukos Corp. No other author has a financial or proprietary interest in any material or method mentioned.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| 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".