A prospective randomized clinical trial comparing nepafenac, intravitreal triamcinolone and no adjuvant therapy for epiretinal membrane
Bibliographic record
Abstract
PURPOSE: To compare the efficacy of topical nepafenac 0.1% versus intravitreal triamcinolone acetonide (IVTA) at the conclusion of vitrectomy surgery versus no adjuvant therapy (NAT) in improving macular morphology post-operatively in patients undergoing vitrectomy for epiretinal membrane (ERM), as measured by optical coherence tomography (OCT) imaging and best-corrected visual acuity (BCVA). METHODS: Design: Prospective randomized clinical trial Setting: Multi-centre 80 patients scheduled to undergo vitrectomy surgery for idiopathic ERM were randomized to receive either IVTA (4 mg/0.1 cc) at the end of surgery, topical nepafenac sodium 0.1% TID for 1 month post-operation or no adjuvant treatment (NAT). Optical coherence tomography (OCT) imaging, best-corrected visual acuity and intraocular pressure (IOP) were measured before surgery, and 1 and 2 months post-operation. RESULTS: Although all three groups showed reduction in macular thickness post-operation, the NAT group showed the most improvement, with a reduction of 136.18 ± 29.84 μm at two months. There was no statistically significant difference in macular thickness between the groups at each time point, p = 0.158. The NAT group also had the best recovery in BCVA with an improvement of 0.207 logMAR (10.35 letters) at two months post-operation. There was no statistically significant difference in BCVA between the groups, p = 0.606. There was statistically significant difference in the IOP between the three groups, p = 0.04 only at 1-month visit. The IVTA group had the highest rise in average IOP at both 1 and 2 months post-operation (2.72 and 1.58 mmHg, respectively). CONCLUSION: Our study data suggest there was no advantage in the use of topical nepafenac or IVTA for post-vitrectomy ERM surgery.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".