Corneal endothelial safety profile in minimally invasive glaucoma surgery
Bibliographic record
Abstract
PURPOSE: To compare 5-year corneal endothelial safety of 3 minimally invasive glaucoma surgery (MIGS) devices (iStent inject , Hydrus Microstent, CyPass Micro-Stent). SETTING: U.S. multicenter trials. DESIGN: Post hoc 5-year analysis from prospective randomized single-masked pivotal trials. METHODS: Mild to moderate open-angle glaucoma subjects received a MIGS implant with phacoemulsification (implant + phaco) or phaco alone (control). In addition, 5-year end points comparing the implant and control groups included proportion of eyes with significant endothelial cell loss (ECL) (>30% or ≥30% vs baseline) and mean endothelial cell density (ECD). RESULTS: Comparable proportions of eyes in the iStent inject + phaco and control groups had significant 60-month ECL (9.4% vs 6.3%, respectively, diff: 3.2%, 95% CI, -5.0% to 11.3%, P = .77). Hydrus (20.8% vs 10.6%, diff: 10.2%, 95% CI, 3.2% to 17.2%, P = .01) and CyPass (27.2% vs 10.0%, diff: 17.2%, 95% CI, 5.6% to 28.7%, P = .02) had more eyes with ECL vs controls (iStent inject 1.49X, Hydrus 1.96X, CyPass 2.72X vs controls). Mean ECD over 60 months for iStent inject was indistinguishable vs control, whereas greater ECL was observed primarily 3 months postoperative (Hydrus) or accelerated after 2 years (CyPass). No iStent inject or Hydrus subjects developed persistent corneal edema, whereas 7 CyPass-implanted eyes developed ECL-related complications. CONCLUSIONS: Through 5 years postoperative, there were no differences in proportion of eyes with significant ECL or mean ECD between the iStent inject and control groups. There was greater 5-year ECL and lower ECD in the Hydrus and CyPass groups vs controls. The Hydrus ECL rate mirrored control after 3 months; the CyPass ECL rate accelerated vs control.
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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 | 0.004 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".