Improved detection of decreased glucose handling capacities via continuous glucose monitoring-derived indices
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 cl...
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Nature Portfolio
2025-04-01
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| Series: | Communications Medicine |
| Online Access: | https://doi.org/10.1038/s43856-025-00819-5 |
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| author | Hikaru Sugimoto Ken-ichi Hironaka Tomoaki Nakamura Tomoko Yamada Hiroshi Miura Natsu Otowa-Suematsu Masashi Fujii Yushi Hirota Kazuhiko Sakaguchi Wataru Ogawa Shinya Kuroda |
| author_facet | Hikaru Sugimoto Ken-ichi Hironaka Tomoaki Nakamura Tomoko Yamada Hiroshi Miura Natsu Otowa-Suematsu Masashi Fujii Yushi Hirota Kazuhiko Sakaguchi Wataru Ogawa Shinya Kuroda |
| author_sort | Hikaru Sugimoto |
| collection | DOAJ |
| description | 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/ ). |
| format | Article |
| id | doaj-art-e9d68cbe82ee4ab8a5502cabb2c9a17b |
| institution | OA Journals |
| issn | 2730-664X |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Communications Medicine |
| spelling | doaj-art-e9d68cbe82ee4ab8a5502cabb2c9a17b2025-08-20T02:20:00ZengNature PortfolioCommunications Medicine2730-664X2025-04-015111210.1038/s43856-025-00819-5Improved detection of decreased glucose handling capacities via continuous glucose monitoring-derived indicesHikaru Sugimoto0Ken-ichi Hironaka1Tomoaki Nakamura2Tomoko Yamada3Hiroshi Miura4Natsu Otowa-Suematsu5Masashi Fujii6Yushi Hirota7Kazuhiko Sakaguchi8Wataru Ogawa9Shinya Kuroda10Department of Biochemistry and Molecular Biology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-kuDepartment of Biological Sciences, Graduate School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-kuDepartment of Diabetes and Endocrinology, Akashi Medical Center, 743-33 Okubo-cho Yagi, AkashiDivision of Diabetes and Endocrinology, Department of Internal Medicine, Kobe University Graduate School of Medicine, 7-5-1 Kusunoki-cho, Chuo-ku, KobeDepartment of Diabetes and Endocrinology, Takatsuki General Hospital, 1-3-13 Kosobe-cho, TakatsukiDivision of Diabetes and Endocrinology, Department of Internal Medicine, Kobe University Graduate School of Medicine, 7-5-1 Kusunoki-cho, Chuo-ku, KobeDepartment of Biological Sciences, Graduate School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-kuDivision of Diabetes and Endocrinology, Department of Internal Medicine, Kobe University Graduate School of Medicine, 7-5-1 Kusunoki-cho, Chuo-ku, KobeDivision of Diabetes and Endocrinology, Department of Internal Medicine, Kobe University Graduate School of Medicine, 7-5-1 Kusunoki-cho, Chuo-ku, KobeDivision of Diabetes and Endocrinology, Department of Internal Medicine, Kobe University Graduate School of Medicine, 7-5-1 Kusunoki-cho, Chuo-ku, KobeDepartment of Biochemistry and Molecular Biology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-kuAbstract 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/ ).https://doi.org/10.1038/s43856-025-00819-5 |
| spellingShingle | Hikaru Sugimoto Ken-ichi Hironaka Tomoaki Nakamura Tomoko Yamada Hiroshi Miura Natsu Otowa-Suematsu Masashi Fujii Yushi Hirota Kazuhiko Sakaguchi Wataru Ogawa Shinya Kuroda Improved detection of decreased glucose handling capacities via continuous glucose monitoring-derived indices Communications Medicine |
| title | Improved detection of decreased glucose handling capacities via continuous glucose monitoring-derived indices |
| title_full | Improved detection of decreased glucose handling capacities via continuous glucose monitoring-derived indices |
| title_fullStr | Improved detection of decreased glucose handling capacities via continuous glucose monitoring-derived indices |
| title_full_unstemmed | Improved detection of decreased glucose handling capacities via continuous glucose monitoring-derived indices |
| title_short | Improved detection of decreased glucose handling capacities via continuous glucose monitoring-derived indices |
| title_sort | improved detection of decreased glucose handling capacities via continuous glucose monitoring derived indices |
| url | https://doi.org/10.1038/s43856-025-00819-5 |
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