RICHMOND, Va. (WRIC) -- A research study from the University of Virginia Center for Diabetes Technology suggests that data from continuous glucose monitors (CGMs) can predict the development of serious complications in people with type 1 diabetes. The research study, published in Jan. 2025, analyzed data from the landmark Diabetes Control and Complications Trial (DCCT) -- a 10-year study involving 1,440 participants. The DCCT, published in 1993, established hemoglobin A1c as the gold standard for assessing diabetes control. By utilizing advanced machine learning techniques, researchers were able to simulate CGM data for each participant throughout the trial. According to UVA Health, the study found that the amount of time patients spent within a safe blood sugar range (between 70 and 180 mg/dL) over a 14-day period was a good of a predictor of complications like blindness, nerve damage and kidney disease as the traditional method using hemoglobin A1c levels. “This is a study that is a first of its kind to the best of our knowledge," said Boris Kovatchev, director of the UVA Center for Diabetes Technology. “Continuous glucose monitoring is relatively new to the field, and is not widely accepted at the level it should be.”  Kovatchev said data from continuous glucose monitoring could help doctors identify patients at higher risk for complications and personalize treatment plans more effectively. He added that virtualizing a clinical trial to fill in the gaps in old data using science methods is the next best thing we can do today. "We hope that it will have implications -- even beyond diabetes, whenever possible -- to amplify existing data or smaller clinical trials to make conclusions and hypothesis-testing cheaper and much faster," Kovatchev said.