Effectiveness and safety of the XEN45 gel stent compared to trabeculectomy in primary open-angle glaucoma: the Gold-Standard Pathway Study
Bibliographic record
Abstract
AIM: To compare the gel stent to trabeculectomy in the Gold-Standard Pathway Study (GPS) patients with primary open-angle glaucoma (POAG). METHODS: In the GPS, patients with elevated intraocular pressure (IOP) poorly controlled with IOP-lowering medication were randomised (2:1, gel stent:trabeculectomy). Aggregate primary endpoint: patients (%) at month 12 achieving ≥20% IOP reduction from baseline without medication increase, clinical hypotony, vision loss to counting fingers or secondary surgical intervention (SSI). Secondary endpoints included changes in mean IOP and medication count from baseline; postoperative interventions; visual recovery; postoperative complications; and the Symptom and Health Problem Checklist (SHPC-18) questionnaire. RESULTS: Of 130 eyes with POAG treated/analysed (gel stent, n=88; trabeculectomy, n=42); 61.4% and 69.0% met the primary endpoint, respectively (p=0.394). At month 12, the change from baseline in mean IOP was statistically greater post-trabeculectomy (by 2.8 mm Hg; p=0.028) than post-gel stent. Postoperative intervention and postoperative complication rates were 39.8% and 75.0% (gel stent) versus 76.2% and 92.9% (trabeculectomy), respectively. Hypotony (IOP ≤6 mm Hg at two consecutive visits) rates were 14.8% (gel stent) and 28.6% (trabeculectomy). Visual recovery was faster/better (per the mean and time to first return to baseline best corrected visual acuity) and SHPC-18-related improvements were greater post-gel stent than post-trabeculectomy. CONCLUSION: Similar proportions of eyes with POAG achieved the primary endpoint post-gel stent and post-trabeculectomy. The mean IOP reduction was statistically greater post-trabeculectomy. The gel stent resulted in fewer postoperative interventions, faster/better visual recovery, favourable patient-reported outcomes and fewer specific adverse events, although more SSIs and IOP elevations were observed.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".