RT Journal Article
T1 Glucodensity functional profiles outperform traditional continuous glucose monitoring metrics
A1 Matabuena, Marcos
A1 Ghosal, Rahul
A1 Aguilar, Javier Enrique
A1 Keshet, Ayya
A1 Wagner, Robert
A1 Fernández Merino, Carmen
A1 Sánchez Castro, Juan
A1 Zipunnikov, Vadim
A1 Onnela, Jukka-Pekka
A1 Gude Sampedro, Francisco
K1 Glucose dynamic
K1 Continuos glucose monitoring
K1 Digital health
K1 Functional data analysis
AB Continuous glucose monitoring (CGM) data have revolutionized the management of type 1 diabetes, particularly when integrated with insulin pumps to mitigate clinical events such as hypoglycemia. Recently, there has been growing interest in utilizing CGM devices in clinical studies involving healthy and diabetic populations. However, efficiently exploiting the high temporal resolution of CGM profiles remains a significant challenge. Numerous indices—such as time–in–range metrics and glucose variability measures–have been proposed, but evidence suggests these metrics overlook critical aspects of dynamic glucose homeostasis. As an alternative method, this paper explores the clinical value of glucodensity metrics in capturing glucose dynamics—specifically the speed and acceleration of CGM time series–as new biomarkers for predicting long-term glucose outcomes. Our results demonstrate significant information gains, exceeding 20 % in terms of adjusted r-square, in forecasting glycosylated hemoglobin (HbA1c) and fasting plasma glucose (FPG) at five and eight years from baseline AEGIS data, compared to traditional non-CGM and CGM glucose biomarkers. These findings underscore the importance of incorporating more complex CGM functional metrics, such as the glucodensity approach, to fully capture continuous glucose fluctuations across different time–scales
PB Springer Nature
SN 2045-2322
YR 2025
FD 2025-09-29
LK https://hdl.handle.net/10347/44558
UL https://hdl.handle.net/10347/44558
LA eng
NO Matabuena, M., Ghosal, R., Aguilar, J.E. et al. Glucodensity functional profiles outperform traditional continuous glucose monitoring metrics. Sci Rep 15, 33662 (2025). https://doi.org/10.1038/s41598-025-18119-2
NO Instituto de Salud Carlos III (ISCIII) through the projects PI11/02219, PI16/01395, PI20/01069
NO Network for Research on Chronicity, Primary Care, and Health Promotion, ISCIII, RD24/0005/0010, co-funded by the European Union (UE)
NO Galician Innovation Agency-Competitive Benchmark Groups (GAIN-GRC/IN607A2025-09/Xunta de Galicia)
DS Minerva
RD 28 abr 2026