Two groundbreaking studies presented at the 83rd Scientific Sessions by the American Diabetes Association® (ADA) in San Diego, CA, have revealed significant advancements in glucose control and the management of diabetic retinopathy. These findings are particularly noteworthy as they coincide with the growing prevalence of smart technology, including artificial intelligence (AI), digital health technology, and innovative medical devices, which are revolutionizing diabetes care and enhancing the quality of life.
Dr. Robert Gabbay, the ADA’s Chief Scientific and Medical Officer, expressed enthusiasm about the progress made in diabetes technology, particularly driven by AI and medical devices. He emphasized the significance of novel technology showcased at the Scientific Sessions, highlighting its potential to transform diabetes care.
The first study focused on a revolutionary device called SynerGTM, developed by Pacific Diabetes Technologies, which combines glucose sensing and insulin delivery functions in a single device. Unlike current technology that requires multiple devices and separate insertions, SynerGTM streamlines diabetes management by synchronizing the replacement schedules for insulin delivery and glucose measurement. The study, titled “Feasibility of a Prototype Dual Function Glucose Sensing Insulin Delivery Cannula in People with Type 1 Diabetes,” involved 24 adults with type 1 diabetes using insulin pump therapy. The results demonstrated the accuracy of the glucose sensor and reliable insulin delivery without interference, marking a significant advancement in glucose level management.
The second study focused on the use of AI algorithms to predict the progression of diabetic retinopathy, a condition expected to affect over 14 million Americans by 2050. Estimating the risk of progression is challenging due to variations in medical knowledge and clinical experience among clinicians. To address this, the study, titled “Identifying the Risk of Diabetic Retinopathy Progression Using Machine Learning on Ultrawide Field Retinal Images,” developed and validated machine learning models for diabetic retinopathy progression using ultrawide field retinal images. The findings demonstrated the accuracy and feasibility of using AI algorithms to identify disease progression, potentially allowing for personalized screening intervals and improved vision-related outcomes.
These studies mark significant advancements in diabetes technology, offering hope for improved diabetes care and enhanced quality of life. The integration of AI, digital health technology, and novel medical devices has the potential to transform the management of diabetes and its related complications.