Virtual reality perimetry compared to standard automated perimetry in adults with glaucoma: A systematic review
Bibliographic record
Abstract
PURPOSE: The purpose of this systematic review was to consolidate and summarize available data comparing virtual reality perimetry (VRP) with standard automated perimetry (SAP) in adults with glaucoma. Understanding the utility and diagnostic performance of emerging VRP technology may expand access to visual field testing but requires evidence-based validation. METHODS: A systematic literature search was conducted in 3 databases (PubMed Central, Embase, and Cochrane Central Register of Controlled Trials) from the date of inception to 10/09/2024. Eligibility criteria included randomized controlled trials or prospective or retrospective cohort studies that compared different modalities of VRP to SAP in adults >18 years of age with glaucoma. Studies were excluded if they were review articles, letters, case reports, abstract-only papers, unavailable full text, or non-English language. Identified studies were formally evaluated for risk of bias using the Newcastle-Ottawa tool. The study protocol was prospectively registered with PROSPERO in May 2023 (registration number: CRD42023429071). RESULTS: The literature search yielded 1657 results. After deduplication, abstract and title screening, 14 studies met inclusion criteria and were included in the final systematic review. Compared to Humphrey Field Analyzer or Octopus 900, 10 different VRP devices were included in our study: Oculus Quest, Smartphone-based Campimetry, Toronto Portable Perimeter, VirtualEye, Advance Vision Analyzer, VisuALL, Vivid Vision Perimeter, C3 fields visual field analyzer, Radius, and Virtual Field. Overall, published studies of VRP are promising; however, more work is required to better evaluate these devices, namely test-retest repeatability. CONCLUSIONS: VRP holds strong potential to evaluate visual fields in adults with glaucoma, though further data is needed to validate emerging technologies and testing protocols. Eye providers may consider using these devices to monitor certain adults with glaucoma.
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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 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.009 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".