Abstract
The glycemia risk index (GRI) is an emerging metric designed to quantify the risk of both hypo- and hyperglycemia, providing a combined assessment of glycemic control quality. A high GRI is associated with an increased risk of diabetic complications. In this study, we leverage long-term continuous glucose monitoring (CGM) data to develop and validate predictive models for a high GRI (>60) in individuals with T1D. We assessed over 250 000 days of measurements collected over four years from 736 patients with type 1 diabetes. Our modeling approach shows promise for predicting glycemic control quality (area under the receiver operating characteristic curve [ROC-AUC] of 0.87) six to nine months from baseline. However, additional analysis and validation are imperative to determine its full clinical utility.