Systematic review and meta-analysis of the clinical effectiveness, safety, humanistic and economic burden of the OMNI <sup>®</sup> surgical system and its predecessors
Bibliographic record
Abstract
Objective The aim of this systematic review and meta-analysis was to assess the clinical, humanistic, and economic evidence of the OMNI ® Surgical System (OMNI), Visco360 and Trab360 for open-angle glaucoma (OAG). Methods Search strategies were applied across MEDLINE ® , Web of Science™, Cochrane (January 2016–April 2024) on 16th April 2024. Congress proceedings (2021–2024) were searched in July 2024. Studies containing ≥15 patients that reported clinical, humanistic or economic outcomes associated with the use of OMNI, Visco360 or Trab360 for the treatment of adults with OAG were included. Structured summaries were used to summarize findings and a meta-analysis synthesized the data. Risk of bias was assessed using the Newcastle-Ottawa and CHEERS checklists. The protocol was registered on PROSPERO (CRD42024536680). Results Among 29 included publications, 27 reported clinical and 2 reported economic outcomes. OMNI significantly reduced intraocular pressure (IOP) with mean IOP <18 mmHg (11.5–17.2 mmHg) at 12 months when used standalone or combined with cataract surgery. The meta-analysis confirmed statistically significant, comparable IOP reductions at months 6, 12 and 24. IOP-lowering medication use decreased from 0.9–3.4 at baseline to 0.1–2.2 at month 12 (standalone and combination) ; these continued months 24–36. Adverse events were generally mild and transient. Conclusion OMNI consistently reduced IOP and medication use demonstrating sustained effects over 24–36 months with a favorable safety profile, thus supporting its use in patients with OAG. Limitations of this review include the absence of randomized controlled trials. Six studies were assessed as good quality, the remainder showed risk of bias.
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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 | 0.026 | 0.058 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.036 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".