Comparison of Visual Recovery Following Ex-PRESS Versus Trabeculectomy
Bibliographic record
Abstract
PURPOSE: To compare the rate of visual recovery after Ex-PRESS implantation versus standard trabeculectomy. PATIENTS AND METHODS: Subjects enrolled in a prospective randomized controlled trial comparing Ex-PRESS to trabeculectomy were analyzed for postoperative changes in visual acuity (VA). Risk factors for visual loss (split fixation, cup-disc ratio, intraocular pressure, visual field mean deviation, and hypotony) were evaluated. RESULTS: Sixty-four subjects were enrolled (33 Ex-PRESS, 31 trabeculectomy). There was no significant difference in mean logMAR VA between groups at baseline or any study visit. VA was significantly reduced up to week 2 following surgery in both the groups. However, by month 1, VA in the Ex-PRESS group was no longer significantly different from baseline (P=0.23) and remained nonsignificant at subsequent visits up to 6 months. In the trabeculectomy group, VA remained significantly lower than baseline at each study visit. At 6 months, 47% of the trabeculectomy eyes compared with 16% of the Ex-PRESS eyes had lost ≥2 Snellen lines (P=0.01). Reasons for VA loss included cataract, central retinal vein occlusion, and diabetic retinopathy, however, in a significant number of cases no cause could be determined. None of the risk factors evaluated were associated with vision loss. CONCLUSIONS: Although there was no difference in mean VA between the Ex-PRESS and trabeculectomy groups at any time point, trabeculectomy eyes were more likely to lose ≥2 Snellen lines. In addition, VA recovered faster in the Ex-PRESS group.
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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 | 0.005 |
| 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 | 0.000 | 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".