The Glaucoma and Retinopathy Screening Study
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: AI-based glaucoma screening, IOP measurement, Virtual Reality Visual Field Testing.
- Who it may be relevant to
- Registry conditions: Glaucoma. Basic parameters: from 40 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- United States
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
Unsure about the terms? Read our patient guide →
Official title
The Glaucoma and Retinopathy Screening Study (GRaSS)
Overview
The goal of this clinical trial is to learn if a new screening approach including an artificial intelligence algorithm that analyzes fundus photographs, measurement of eye pressure and visual field testing works to screen for glaucoma. Participants will: Have an image of their fundus (back of the eye) taken as part of their diabetic eye screening Have a measurement of their eye pressure If needed, have a test of their side vision using a headset
Detailed description
Study Overview: This study is a prospective, interventional clinical trial designed to evaluate the effectiveness of an artificial intelligence (AI)-based screening program within community health settings. This study targets especially diabetic patients because they have higher risks of developing glaucoma. By integrating glaucoma screening into existing diabetic eye disease (DED) screenings, the study aims to identify cases of glaucoma earlier, thereby preventing or delaying progression to blindness.
Background: Glaucoma is a chronic eye disease that causes progressive optic nerve damage, often leading to irreversible vision loss. Early detection is critical, as glaucoma is typically asymptomatic in its early stages. Individuals with diabetes are at an elevated risk for glaucoma, making it crucial to develop accessible screening methods. Current DED screening programs already utilize fundus photography for diabetic retinopathy. Adding glaucoma screening to these existing DED screenings may provide an efficient and cost-effective solution to reach high-risk populations without requiring additional clinic visits.
Study Hypothesis: The hypothesis of this study is that incorporating AI-driven glaucoma screening into standard DED screenings will increase the detection rate of glaucoma in high-risk populations compared to DED screening alone. This combined approach is expected to yield better clinical outcomes by enabling early diagnosis and treatment while being cost-effective.
Expected Outcomes and Impact: This study is expected to provide valuable insights into the effectiveness of integrating AI-based glaucoma screening into existing screening programs for diabetic eye disease. If successful, this combined screening approach could be a cost-effective model for other community health settings, leading to earlier detection of glaucoma and improved patient outcomes. By making glaucoma screening more accessible the study aims to reduce health disparities and support preventive eye care.
Interventions
- Device AI-based glaucoma screening
AI analysis of fundus photographs to detect signs of glaucoma, added to AI-based diabetic eye disease screening performed for routine clinical care - Device IOP measurement
Intraocular pressure measurement by Icare tonometer - Device Virtual Reality Visual Field Testing
Virtual Reality Visual Field Testing by the Olleyes device for participants suspected of having glaucoma
Primary outcome measures
- Glaucoma detection [Time frame: 1 year from initial screening]
Secondary outcome measures (3)
- Cost-Effectiveness of Combined Screening vs. DED-Only Screening [Time frame: 1 year from initial screening]
- Participant Satisfaction with Screening Process [Time frame: Day of screening]
- Participant knowledge about glaucoma [Time frame: Day of screening]
Eligibility criteria
- Individuals with diabetes undergoing AI-based screening for diabetic retinopathy using the LumineticsCore (Digital Diagnostics) system for clinical care at primary care centers.
- Individuals who are able and willing to provide informed consent for participation in the study.
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: No
Study design
- Allocation
- Non-randomized
- Model
- Parallel assignment
- Masking
- Open label
- Primary purpose
- Screening
Study locations
United States · 5 centers
- Brigham and Women's Primary Care Associates of Longwood — Boston
- MGH Chelsea HealthCare Center — Chelsea
- NSPG Lynn — Lynn
- NSPG Salem — Salem
- NSPG Saugus — Saugus
Identifiers
NCT: NCT06882356 · 2024p003709