Impact of Ophthalmic Viscosurgical Devices in Cataract Surgery
Bibliographic record
Abstract
BACKGROUND: Ophthalmic viscoelastic devices (OVDs) used during small-incision cataract surgery have numerous advantages. However, OVDs have longer retention time in an eye after surgery resulting in intraocular pressure (IOP) spikes. The purpose of this study is to analyze and quantify the effect of various OVDs on both IOP and best corrected visual acuity (BCVA) by systematically reviewing the literature and performing meta-analysis. METHODS: Numerous databases from January 1, 1985, to present were systematically searched. Thirty-six (3893 subjects) of 3313 studies identified were included for analysis. Standardized mean difference (SMD) was computed, and meta-analysis was performed. RESULTS: A total of 3313 records were retrieved including 1114 from database search and 2199 from grey literature search. Significant increase in postoperative IOP in 1-day follow-up with Healon (SMD = 0.37, CI: [0.07, 0.67]), Viscoat (SMD = 0.29, CI: [0.13, 0.45]), Provisc (SMD = 0.46, CI: [0.17, 0.76]), and Soft Shell (SMD = 0.58, CI: [0.30, 0.86]) was computed. On the other hand, results implied a nonsignificant increase in postoperative IOP with Healon GV (SMD = 0.07, CI: [-0.28, 0.41]), Healon5 (SMD = 0.15, CI: [-0.33, 0.64]), 2% HPMC (SMD = 0.32, CI: [-0.0, 0.64]), and OcuCoat (SMD = 0.26, CI: [-0.37, 0.9]). Additionally, a nonsignificant reduction in postoperative IOP was inferred with Viscoat + Provisc (SMD = -0.28, CI: [-2.23, 1.68]). CONCLUSION: Improvement in IOP was shown with Viscoat + Provisc. Additionally, IOP nonsignificant upsurge was observed with Healon GV, Healon5, 2% HPMC, and OcuCoat compared to significant upsurge with Healon, Viscoat, and Soft Shell.
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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 | 0.008 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.015 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".