Lynn

Researchers are evaluating if a new screening method that uses an artificial intelligence AI algorithm to analyze fundus photographs, combined with eye pressure measurement and visual field testing, can improve glaucoma screening. This study focuses on people with diabetes, who have a higher risk of glaucoma, by adding glaucoma screening to existing diabetic eye disease DED screenings. The goal is to detect glaucoma earlier to help prevent or delay vision loss. Participants will be assigned to one of two groups. One group will have fundus photographs analyzed by AI for signs of glaucoma and diabetic retinopathy, plus their intraocular pressure measured using an Icare tonometer. If glaucoma is suspected, they will also undergo virtual reality visual field testing using the Olleyes device. The other group will receive usual care with diabetic eye disease screening only, including AI assessment for diabetic retinopathy without additional glaucoma tests. During the study, participants will have their eye images taken, eye pressure measured, and if needed, visual field tested using a headset. Researchers will track how well glaucoma is detected within one year of the initial screening. They will also evaluate the cost-effectiveness of the combined screening, participant satisfaction, and knowledge about glaucoma. The study is conducted in community health settings and aims to make glaucoma screening more accessible and integrated with routine diabetic eye care.