Background: The Glycemia Risk Index (GRI) was introduced as a single value derived from the ambulatory glucose profile that identifies patients who need attention. This study describes participants in each of the five GRI zones and examines the percentage of variation in GRI scores that is explained by sociodemographic and clinical variables among diverse adults with type 1 diabetes.
Methods: A total of 159 participants provided blinded continuous glucose monitoring (CGM) data over 14 days (mean age [SD] = 41.4 [14.5] years; female = 54.1%, Hispanic = 41.5%). Glycemia Risk Index zones were compared on CGM, sociodemographic, and clinical variables. Shapley value analysis examined the percentage of variation in GRI scores explained by different variables. Receiver operating characteristic curves examined GRI cutoffs for those more likely to have experienced ketoacidosis or severe hypoglycemia.
Results: Mean glucose and variability, time in range, and percentage of time in high, and very high, glucose ranges differed across the five GRI zones ( values < .001). Multiple sociodemographic indices also differed across zones, including education level, race/ethnicity, age, and insurance status. Sociodemographic and clinical variables collectively explained 62.2% of variance in GRI scores. A GRI score ≥84.5 reflected greater likelihood of ketoacidosis (area under the curve [AUC] = 0.848), and scores ≥58.2 reflected greater likelihood of severe hypoglycemia (AUC = 0.729) over the previous six months.
Conclusions: Results support the use of the GRI, with GRI zones identifying those in need of clinical attention. Findings highlight the need to address health inequities. Treatment differences associated with the GRI also suggest behavioral and clinical interventions including starting individuals on CGM or automated insulin delivery systems.
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http://dx.doi.org/10.1177/19322968231164151 | DOI Listing |
J Diabetes Sci Technol
January 2025
Division of Endocrinology and Metabolism, Department of Medicine, Samsung Medical Center, Sungkyunkwan University, School of Medicine, Seoul, Republic of Korea.
Background: The glycemia risk index (GRI) is a novel composite continuous glucose monitoring (CGM) metric composed of hypoglycemia and hyperglycemia components and is weighted toward extremes. This study aimed to investigate the association between GRI and the risk of albuminuria in type 1 diabetes.
Methods: The 90-day CGM tracings of 330 individuals with type 1 diabetes were included in the analysis.
J Diabetes Sci Technol
October 2024
Division of Endocrinology and Metabolism, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
Background: The glycemia risk index (GRI) is a new composite continuous glucose monitoring (CGM) metric for weighted hypoglycemia and hyperglycemia. We evaluated the association between the GRI and cardiovascular autonomic neuropathy (CAN) and compared the effects of the GRI and conventional CGM metrics on CAN.
Methods: For this cross-sectional study, three-month CGM data were retrospectively analyzed before autonomic function tests were performed in 165 patients with type 1 diabetes.
Diabetes Technol Ther
October 2023
Division of Pediatric Endocrinology and Diabetes, Koc University School of Medicine, Istanbul, Turkey.
The Glycemia Risk Index (GRI) and Continuous Glucose Monitoring Index (COGI) are newly defined composite metric parameters derived from continuous glucose monitoring (CGM) data. GRI is divided into five separate risk zones (from lowest to highest: A-E). In this study, the effect of the advanced hybrid closed loop (AHCL) system on GRI and COGI in children with type 1 diabetes was evaluated.
View Article and Find Full Text PDFDiabetes Obes Metab
November 2023
Barbara Davis Center for Diabetes, University of Colorado, Aurora, Colorado, USA.
Aim: To evaluate the glycaemia risk index (GRI) and its association with other continuous glucose monitoring (CGM) metrics after initiation of an automated insulin delivery (AID) system in patients with type 1 diabetes (T1D).
Materials And Methods: Up to 90 days of CGM data before and after initiation of an AID system from 185 CGM users with T1D were collected. GRI and other CGM metrics were calculated using cgmanalysis R software and were analysed for 24 hours, for both night-time and daytime.
J Diabetes Sci Technol
September 2024
Chan Division of Occupational Science and Occupational Therapy, University of Southern California, Los Angeles, CA, USA.
Background: The Glycemia Risk Index (GRI) was introduced as a single value derived from the ambulatory glucose profile that identifies patients who need attention. This study describes participants in each of the five GRI zones and examines the percentage of variation in GRI scores that is explained by sociodemographic and clinical variables among diverse adults with type 1 diabetes.
Methods: A total of 159 participants provided blinded continuous glucose monitoring (CGM) data over 14 days (mean age [SD] = 41.
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