Study finds patients with a higher degree of retinopathy severity had worse cardiovascular outcomes.
Read More »Predicting Vision Loss in Patients with Type 2 Diabetes
Could the visual disturbances that diabetes patients experience be prevented?
Read More »Vision Loss Avoidable
Surveys indicate that eyesight is the one sense that Americans fear losing most. Several weeks ago, I examined a patient who complained of "sudden" onset vision loss....
Read More »How to Reduce the Risk of Diabetic Retinopathy
Study examines effect of statins in diabetic retinopathy risk for type 2 diabetes patients.
Read More »Glycemic Threshold Differs By Ethnicity For Development Of Diabetic Retinopathy
Specific A1c, glucose ranges associated with diabetes-specific vision impairment.
Read More »Glycemic Variability and Development of Retinopathy
Study assesses glycemic variability via continuous glucose monitoring and compares it against incidence of diabetic retinopathy to determine if correlation exists.
Read More »More Reasons To Use Statins For Diabetes Treatment
Development of diabetic retinopathy found to be significantly reduced.
Read More »GLP-1 Agonists Do Not Increase Risk for Diabetic Retinopathy
New findings compare treatment with patients taking two or more glucose-lowering agents.
Read More »Point: FDA Approves Artificial Intelligence (AI) To Detect Retinopathy
Software provides screening decision without need for a clinician to interpret image or results.
Read More »Counterpoint: The Pros and Cons of AI-based “Diagnosis” of Diabetic Retinopathy
By A. Paul Chous, MA, OD, FAAO, CDE
The FDA just gave first approval to an artificial intelligence (AI) algorithm for the detection of diabetic retinopathy in the offices of non-ophthalmic health care practitioners. Dubbed the IDx-DR (IDx, LLC, Coralville, Iowa), and paired with a Topcon NW400 non-mydriatic retinal camera, captured images are sent to a cloud-based server that utilizes the IDx-DR software and a ‘deep learning’ algorithm to detect retinal findings consistent with diabetic retinopathy based on autonomous comparison with a large dataset of representative fundus images.