Researchers develop data-based model that accurately estimates A1c using self-monitored blood glucose

Hemoglobin A1c is the standard measurement for assessing glycemic control over time in people with diabetes. Blood levels of A1c are typically measured every few months in a laboratory, but now researchers have developed a data-based model that accurately estimates A1c using self-monitored blood glucose (SMBG) readings, as described in Diabetes Technology & Therapeutics (DTT), a peer-reviewed journal from Mary Ann Liebert, Inc., publishers. The article is available free on the DTT website at http://www.liebertpub.com/dtt.

In "Accuracy and Robustness of Dynamical Tracking of Average Glycemia (A1c) to Provide Real-Time Estimation of Hemoglobin A1c Using Routine Self-Monitored Blood Glucose Data," authors Boris Kovatchev, PhD, Frank Flacke, PhD, Jochen Sieber, MD, and Marc Breton, PhD present the computer algorithm they developed based on a training data set drawn from 379 subjects and then evaluated for accuracy on an independent test data set. The authors propose that estimation of real-time A1c could increase individuals' motivation to improve diabetes control.

"Patients are used to an A1c result from their doctor visits, and this study highlights simple estimated A1c values from SMBG data," says Satish Garg, MD, Editor-in-Chief of Diabetes Technology & Therapeutics and Professor of Medicine and Pediatrics at the University of Colorado Denver. "This may become an important tool for improved patient self-management."