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Feasibility of digital phenotyping based on continuous glucose monitoring to support personalized lifestyle medicine in type 2 diabetes
被引:0
|作者:
van den Brink, Willem J.
[1
]
van den Broek, Tim J.
[1
]
Wopereis, Suzan
[1
]
Difrancesco, Sonia
[1
]
van der Horst, Frans A. L.
[2
]
de Hoogh, Iris M.
[1
,3
]
机构:
[1] Unit Hlth Living & Work, Netherlands Org Appl Sci Res TNO, Sylviusweg 71, NL-2333 BE Leiden, Netherlands
[2] Reinier Med Diagnost Ctr, Dept Clin Chem, Reinier Graafweg 7, NL-2625 AD Delft, Netherlands
[3] Leiden Univ Med Ctr LUMC, Dept Internal Med, Albinusdreef 2, NL-2333 ZA Leiden, Netherlands
来源:
关键词:
Continuous glucose monitoring;
Digital biomarkers;
Personalized medicine;
Diabetes subtypes;
Oral glucose tolerance test;
GLYCEMIC VARIABILITY;
DISPOSITION INDEX;
MUSCLE;
D O I:
10.1016/j.maturitas.2024.108188
中图分类号:
R592 [老年病学];
C [社会科学总论];
学科分类号:
03 ;
0303 ;
100203 ;
摘要:
Objectives: Type 2 diabetes is a highly prevalent age-related chronic condition, with complex and heterogeneous pathogenesis. A 5-point oral glucose tolerance test can identify type 2 diabetes subtypes or "diabetypes" based on the degree of insulin resistance in muscle and/or liver, and beta-cell dysfunction. Due to its costly and invasive nature, the oral glucose tolerance test is not scalable. Presuming that differences in glucose and insulin dynamics manifest in continuous glucose monitoring profiles, we explore the potential of continuous glucose metrics to replace the oral glucose tolerance test for diabetyping. Study design: In a prospective intervention study, 41 people with type 2 diabetes on lifestyle and/or metformin treatment wore a continuous glucose monitor during 3 control periods of 4 days. During each control period, participants underwent a 5-point oral glucose tolerance test after an overnight fast. Main outcome measures: Continuous glucose monitoring data from the control periods, excluding the day of the oral glucose tolerance test, was retrospectively analyzed for associations with diabetypes, as well as Spearman correlations between bootstrapped continuous glucose features, including physiology-based and other time- series features, and oral glucose tolerance metrics. Results: Significant associations were observed between continuous glucose metrics (e.g., low and high blood glucose index, eA1c, and glucose excursions) and oral glucose tolerance metrics (e.g., 2-h glucose, disposition index, insulinogenic index). Furthermore, data-driven metrics (e.g., maximum shift, lumpiness) showed more selective correlations, indicating that data-driven metrics may contain additional information associated with oral glucose tolerance metrics. Conclusions: These results indicate the potential of continuous glucose monitoring to replace the oral glucose tolerance test for diabetyping, driving proactive and personalized (lifestyle) treatment. Netherlands trial register: NL7848
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