TY - JOUR
T1 - Glycemic Risk Index Profiles and Predictors Among Diverse Adults With Type 1 Diabetes
AU - Hoogendoorn, Claire J.
AU - Hernandez, Raymond
AU - Schneider, Stefan
AU - Harmel, Mark
AU - Pham, Loree T.
AU - Crespo-Ramos, Gladys
AU - Agarwal, Shivani
AU - Crandall, Jill
AU - Peters, Anne L.
AU - Spruijt-Metz, Donna
AU - Gonzalez, Jeffrey S.
AU - Pyatak, Elizabeth A.
N1 - Publisher Copyright:
© 2023 Diabetes Technology Society.
PY - 2023
Y1 - 2023
N2 - 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 (P 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.
AB - 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 (P 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.
KW - automated insulin delivery systems
KW - continuous glucose monitoring
KW - diabetes self-management
KW - glycemic risk index
KW - health inequities
KW - type 1 diabetes
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U2 - 10.1177/19322968231164151
DO - 10.1177/19322968231164151
M3 - Article
C2 - 36999215
AN - SCOPUS:85152572778
SN - 1932-2968
JO - Journal of Diabetes Science and Technology
JF - Journal of Diabetes Science and Technology
ER -