One-Year Outcomes of Second-Generation Trabecular Micro-Bypass Stents (iStent Inject) Implantation with Cataract Surgery in Different Glaucoma Subtypes and Severities
Bibliographic record
Abstract
PURPOSE: ) with concomitant cataract surgery in various subtypes and severities of glaucoma. METHODS: This single-surgeon, consecutive case series from a Canadian academic ophthalmology center included subjects with cataract, glaucoma, and the need to reduce intraocular pressure (IOP) and/or medications. The 12-month outcomes included mean IOP and medication burden as well as the proportions of eyes with IOP ≤ 18, ≤ 15, and ≤ 12 mmHg compared to baseline. Other measures included corrected distance visual acuity (CDVA), cup-to-disc ratio (CDR), visual field mean deviation (VF MD), retinal nerve fiber layer (RNFL) thickness, ganglion cell inner plexiform layer (GCIPL) thickness, and adverse events. RESULTS: In 118 eyes, mean IOP reduced from 17.00 ± 3.82 mmHg preoperatively to 13.97 ± 2.65 mmHg at the 12-month follow-up mark (17.8% reduction, p < 0.001), and mean medication burden decreased from 2.31 ± 1.33 preoperatively to 1.03 ± 1.10 medications (56% reduction, p < 0.001). After 12 months, 93% of eyes achieved IOP ≤ 18 mmHg (versus 69% preoperatively), 70% of eyes achieved IOP ≤ 15 mmHg (versus 42% preoperatively), and 29% of eyes achieved IOP ≤ 12 mmHg (versus 7% preoperatively). For all eyes, topical medications were either maintained or decreased from baseline, with ≥ 1 medication eliminated from the preoperative regimen for 83% of eyes and ≥ 2 medications eliminated for 36% of eyes. Visual acuity improved significantly, consistent with expectations for cataract surgery, while CDR, VF MD, and RNFL and GCIPL thicknesses remained stable. Safety was favorable, with no intraoperative complications and few transient adverse events postoperatively. CONCLUSION: iStent Inject implantation with cataract surgery safely reduced IOP and medication burden in a real-world clinical population with mild to severe glaucoma, and stabilized visual field, as well as RNFL and GCIPL thicknesses on OCT. FUNDING: The Rapid Service Fees were funded by Glaukos Corporation.
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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 | 0.001 |
| 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) | 0.002 | 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".