2025-04-22 東京大学
<関連情報>
持続グルコースモニタリングに由来する指標によるグルコース処理能力低下の検出の改善 Improved detection of decreased glucose handling capacities via continuous glucose monitoring-derived indices
Hikaru Sugimoto,Ken-ichi Hironaka,Tomoaki Nakamura,Tomoko Yamada,Hiroshi Miura,Natsu Otowa-Suematsu,Masashi Fujii,Yushi Hirota,Kazuhiko Sakaguchi,Wataru Ogawa & Shinya Kuroda
Communications Medicine Published:22 April 2025
DOI:https://doi.org/10.1038/s43856-025-00819-5
Abstract
Background
Efficiently assessing glucose handling capacity is a critical public health challenge. This study assessed the utility of relatively easy-to-measure continuous glucose monitoring (CGM)-derived indices in estimating glucose handling capacities calculated from resource-intensive clamp tests.
Methods
We conducted a prospective study of 64 individuals without prior diabetes diagnosis. The study performed CGM, oral glucose tolerance tests (OGTT), and hyperglycemic and hyperinsulinemic-euglycemic clamp tests. We validated CGM-derived indices characteristics using an independent dataset from another country and mathematical models with simulated data.
Results
A CGM-derived index reflecting the autocorrelation function of glucose levels (AC_Var) is significantly correlated with clamp-derived disposition index (DI), a well-established measure of glucose handling capacity and predictor of diabetes onset. Multivariate and machine learning models indicate AC_Var’s contribution to predicting clamp-derived DI independent from other CGM-derived indices. The model using CGM-measured glucose standard deviation and AC_Var outperforms models using commonly used diabetes diagnostic indices, such as fasting blood glucose, HbA1c, and OGTT measures, in predicting clamp-derived DI. Mathematical simulations also demonstrate the association of AC_Var with DI.
Conclusions
CGM-derived indices, including AC_Var, serve as valuable tools for predicting glucose handling capacities in populations without prior diabetes diagnosis. We develop a web application that calculates these CGM-derived indices (https://cgm-ac-mean-std.streamlit.app/).
Plain language summary
Diabetes is a chronic disease in which the body cannot effectively use a molecule called insulin or does not produce enough insulin. Insulin is a hormone that regulates a type of sugar called glucose. Early detection of impaired insulin-mediated glucose regulation can be used to predict the onset of diabetes and its complications. This study investigated whether continuous glucose monitors, which are less invasive than those commonly used to diagnose diabetes, could be useful in detecting impaired glucose regulation. Our results suggest that continuous glucose monitoring data could serve as a valuable, less invasive alternative for assessing glucose control in individuals without diagnosed diabetes, allowing for better diagnosis and monitoring of these individuals.
