Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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RECRUITING
NA
2000 participants
INTERVENTIONAL
2025-07-16
2030-09-30
Brief Summary
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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
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Detailed Description
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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.
Conditions
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Study Design
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NON_RANDOMIZED
PARALLEL
SCREENING
NONE
Study Groups
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Combined DED and Glaucoma Screening
Participants in this arm will have fundus photographs that are taken as a part of standard clinical care analyzed by AI for signs of glaucoma in addition to for diabetic retinopathy. They will also have intraocular pressure measured. If the AI detects possible glaucoma, participants will undergo virtual perimetry testing for further assessment.
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
IOP measurement
Intraocular pressure measurement by Icare tonometer
Virtual Reality Visual Field Testing
Virtual Reality Visual Field Testing by the Olleyes device for participants suspected of having glaucoma
DED Screening Only (Control Arm)
Participants in this arm will undergo diabetic eye disease (DED) screening only for routine clinical care. This includes fundus photography for AI assessment of signs of diabetic retinopathy.
No interventions assigned to this group
Interventions
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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
IOP measurement
Intraocular pressure measurement by Icare tonometer
Virtual Reality Visual Field Testing
Virtual Reality Visual Field Testing by the Olleyes device for participants suspected of having glaucoma
Eligibility Criteria
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Inclusion Criteria
* Individuals who are able and willing to provide informed consent for participation in the study.
40 Years
ALL
No
Sponsors
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Centers for Disease Control and Prevention
FED
Massachusetts Eye and Ear Infirmary
OTHER
Responsible Party
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David Steven Friedman
Professor of Ophthalmology
Principal Investigators
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David S Friedman, MD, PhD, MPH
Role: PRINCIPAL_INVESTIGATOR
Massachusetts Eye and Ear
Locations
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Brigham and Women's Primary Care Associates of Longwood
Boston, Massachusetts, United States
MGH Chelsea HealthCare Center
Chelsea, Massachusetts, United States
NSPG Lynn
Lynn, Massachusetts, United States
NSPG Salem
Salem, Massachusetts, United States
NSPG Saugus
Saugus, Massachusetts, United States
Countries
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Central Contacts
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Facility Contacts
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Other Identifiers
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2024p003709
Identifier Type: -
Identifier Source: org_study_id
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