Five-Year Visual Field Outcomes of the HORIZON Trial
Bibliographic record
Abstract
PURPOSE: To compare visual field (VF) progression between glaucoma patients receiving cataract surgery alone (CS) or with a Hydrus microstent (CS-HMS). DESIGN: Post hoc analysis of VF data from the HORIZON multicenter randomized controlled trial. METHODS: A total of 556 patients with glaucoma and cataract were randomized 2:1 to either CS-HMS (369) or CS (187) and followed up for 5 years. VF was performed at 6 months and then every year after surgery. We analyzed data for all participants with at least 3 reliable VFs (false positives < 15%). Average between-group difference in rate of progression (RoP) was tested using a Bayesian mixed model and a 2-sided Bayesian P value <.05 (main outcome). A multivariable model measured the effect of intraocular pressure (IOP). A survival analysis compared the probability of global VF sensitivity dropping by predefined cutoffs (2.5, 3.5, 4.5, and 5.5 dB) from baseline. RESULTS: Data from 352 eyes in the CS-HMS arm and 165 in the CS arm were analyzed (2966 VFs). The mean RoP was -0.26 dB/y (95% credible interval -0.36, -0.16) for CS-HMS and -0.49 dB/y (95% credible interval -0.63, -0.34) for CS. This difference was significant (P = .0138). The difference in IOP only explained 17% of the effect (P < .0001). Five-year survival analysis showed an increased probability of VF worsening by 5.5 dB (P = .0170), indicating a greater proportion of fast progressors in the CS arm. CONCLUSIONS: CS-HMS has a significant effect on VF preservation in glaucoma patients compared with CS alone, reducing the proportion of fast progressors.
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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 | 0.003 | 0.006 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".