Four‐year results of a minimally invasive transscleral glaucoma gel stent implantation in a prospective multi‐centre study
Bibliographic record
Abstract
IMPORTANCE: The transscleral XEN Glaucoma Gel Microstent (XEN-GGM, Allergan Plc., Parsippany, New Jersey) is implanted by a minimally invasive ab interno technique. BACKGROUND: The present study aims to assess the long-term clinical outcomes in patients after XEN-GGM implantation. DESIGN: This prospective, non-randomized, multi-centred study was conducted in three countries (Austria, Canada and Germany). PARTICIPANTS: Sixty-four consecutive eyes of 64 patients with open angle glaucoma received the XEN-GGM (63 μm) without Mitomycin C. Thirty-five (55%) were solo procedures, and 29 (45%) were combined with cataract surgery. METHODS: Visits were planned at baseline, 6 months, 1, 2, 3 and 4 years postoperatively. MAIN OUTCOME MEASURES: The main outcome measures were mean intraocular pressure (IOP), mean number of IOP lowering medication. Secondary outcome parameters were: visual acuity, visual fields and complete surgical failure (defined as presence of a secondary IOP lowering procedure or loss of light perception) at 4 years, postoperatively. RESULTS: Mean best-medicated baseline IOP was 22.5 ± 4.2 mmHg and decreased significantly to 13.4 ± 3.1 mmHg 4 years postoperatively (-40%, n = 34, P < 0.001). Mean number of IOP lowering medication decreased significantly from 2.4 ± 1.3 preoperatively to 1.2 ± 1.3 (-50%, n = 34, P < 0.001) postoperatively. Visual field mean deviation showed no significant change between preoperative and postoperative examinations. Complete surgical failure rate per year was 10%. CONCLUSIONS AND RELEVANCE: The XEN-GGM resulted in lower IOP and a reduction in medications from baseline over 4 years of follow-up. There was no detectable decrease in visual fields over the study. The surgical failure rate is comparable to other filtration surgeries.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| 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 | 0.001 |
| 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".