Five-year outcomes of a Schlemm’s canal microstent (Hydrus Microstent) with cataract surgery in open angle glaucoma: real-world results
Bibliographic record
Abstract
OBJECTIVE: To report 5-year real-world outcomes of Hydrus Microstent implantation with cataract surgery (Hydrus+CS) in mild to severe open-angle glaucoma (OAG). DESIGN: A retrospective, consecutive case series. PARTICIPANTS: OAG eyes undergoing Hydrus+CS with 5-year follow-up. METHODS: The primary outcome was surgical success using various criteria based on intraocular pressure (IOP) thresholds (≤21, ≤18, and ≤15 mm Hg), stability or reduction in antiglaucoma medication (AGM) use, and absence of secondary glaucoma surgery. Predictors of failure were analyzed using Cox proportional hazard models. Secondary outcomes included changes in IOP, AGM use, vision, and optic nerve structural measures. RESULTS: Sixty-four OAG eyes with a baseline IOP of 17.8 ± 4.6 mm Hg on 2.8 ± 1.1 AGMs were included. Surgical success ranged from 91% to 25%, depending on the criteria. Six eyes (9%) required secondary glaucoma surgery, and selective laser trabeculoplasty (SLT) was performed in 41% of these cases. AGM use decreased without IOP increases in 56% of eyes. Success rates for those maintaining the same or fewer AGMs at IOP thresholds of ≤21, ≤18, and ≤15 mm Hg were 75%, 70%, and 58%, respectively. For those with reduced AGM use, success rates were 61%, 58%, and 45% at the same thresholds. Predictors of failure included higher preoperative IOP (p < 0.001) and post-operative IOP spikes (p = 0.010). IOP decreased by 26%, from 17.8 mm Hg at baseline to 13.2 mm Hg at 5 years, with AGM use declining from 2.8 to 2.2 medications (p < 0.001). CONCLUSIONS: This study provides the longest follow-up data on Hydrus+CS, confirming its safety and efficacy in mild to severe OAG.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".