Long-Term Follow-Up Study of RGX-314 Administered in the Suprachoroidal Space for Participants With...
Diabetic RetinopathyDRThis is a prospective, observational study designed to evaluate the long-term safety and efficacy of RGX-314. Eligible participants are those who were previously enrolled in a clinical study of DR without center involved-diabetic macular edema (CI-DME) in which they received SCS administration of RGX-314. Enrollment of each participant in the current study should occur after the participant has completed either the end of study or early discontinuation visit in the previous (parent) clinical study. Participants will be followed for a total of 5 years post-RGX-314 administration (inclusive of the parent study). As such, the total study duration for each participant may vary depending on when they enroll in the current study following RGX-314 administration in the parent study.
Smartphone Screening for Eye Diseases
Diabetes MellitusGlaucoma4 moreTo validate new screening instruments for eye disease, increase eye care access in underserved communities, and provide a scientifically implemented method to set up programs for eye disease screening.
VISUPRIME® Eye Drops
Macular DegenerationAge Related4 moreThe study purpose is to assess the efficacy of VISUPRIME® eye drops in preventing the conjunctival bacterial load in patients undergoing to anti-VEGF injection.
UK Imaging Diabetes Study Seeing Diabetes Clearly
Type2 DiabetesDiabetic RetinopathyProspective, observational cohort study to cross-sectionally assess the health of multiple organs, using multiparametric abdominal magnetic resonance imaging (MRI) scan, and understand if resulting MRI metrics can predict future clinical events over a period of 10 years, in patients diagnosed with type 2 diabetes and concurrent diabetic retinopathy (as per their standard of care).
Evaluation of NeoRetina Artificial Intelligence Algorithm for the Screening of Diabetic Retinopathy...
Diabetic RetinopathyDiabetic Macular Edema1 moreThis prospective study aims to validate if NeoRetina, an artificial intelligence algorithm developped by DIAGNOS Inc. and trained to automatically detect the presence of diabetic retinopathy (DR) by the analysis of macula centered eye fundus photographies, can detect this disease and grade its severity.
Screening for Diabetic Retinopathy in Pharmacies With Artificial Intelligence Enhanced Retinophotography...
Diabetic RetinopathyArtificial Intelligence1 moreDiabetic retinopathy is frequent, potentially severe with visual threat, health costly and represents a major public health problem. However, screening compliance for retinopathy remains too low in France, approximately 40% patients with diabetes laking diabetic retinopathy screening for at least 2 years. DIABeyeIA is a prospective pilot study evaluating the effectiveness and acceptability of diabetic retinopathy screening in 11 pharmacies in Normandy (north of France) using a non-mydriatic portable retinophotograph enhanced by artificial intelligence software. The main goal of this work is to evaluate a potential increase rate of diabetic retinopathy screening, compared to the actual rate (64% in France). Secondary goals are faisability, satisfaction and economical considerations for implementation of such a new screening program.
Feasibility and Safety of MB-102 in Ocular Angiography as Compared to Fluorescein Sodium
RetinopathyRetinal Vein Occlusion2 moreThe objective of this study is to evaluate the safety and image quality of the investigational dye, MB-102, compared to the control dye (fluorescein sodium) in healthy and diseased eyes using fluorescent angiography for retinal vascular disease diagnosis and monitoring.
Application of Artificial Intelligence in Early Detection of Eye Complications in Diabetics
Artificial IntelegenceDiabetic Retinopathy Associated With Type 2 Diabetes Mellitus1 moreThe goal of this pragmatic trial is to test the benefit of using artificial intelligence-based eye screening i.e, a fundus camera device in the early detection of eye complications in diabetics. The main questions it aims to answer are: To what extent does the application of artificial intelligence-based eye care at primary care clinics work well in achieving early detection of eye complications such as macular oedema? To what extent does the application of artificial intelligence-based eye care at primary care clinics work well in achieving early detection of eye complications such as retinopathy? Participants will be asked to participate in the screening for eye complications at primary care centres, and a fundus camera will be used for screening. Researchers will compare the proportion of detected cases with early signs of eye complication among those using artificial intelligence-based eye screening i.e., fundus camera, to the proportion of detected cases among those using routine eye care clinics at the primary care centre. Early detection of eye complications in diabetics prevents the risk of blindness.
Analysis of FAZ in Diabetic Retinopathy Using OCT Angiography
Diabetic RetinopathyStudy and assessment of characteristic changes in foveal avascular zone during different stages of diabetic retinopathy using OCTA.
Project Open - Use of Administrative Health Data to Increase Diabetic Retinopathy Screening
DiabetesDiabetic RetinopathyEarly detection through regular diabetic retinopathy screening (DRS) is an effective method of preventing vision loss by enabling earlier intervention and timely treatment. It is recommended that all people with diabetes receive regular DRS, either annually or bi-annually. Current DRS practice in Canada, however, falls remarkably short of recommended DRS rates resulting in preventable vision loss. In this project the investigators use population health-based approach to diabetes care. Linked provincial administrative data will be leveraged to consistently identify all those that have not had DRS in 425 days with the goal to improve outcomes, equity and potentially reduce the cost of care delivery.