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The route to diabetes: Loss of complexity in the glycemic profile from health through the metabolic syndrome to type 2 diabetes

Authors Churruca J, Vigil L, Luna E, Ruiz-Galian J, Varela M

Published 11 August 2008 Volume 2008:1 Pages 3—11

DOI https://doi.org/10.2147/DMSO.S3812

Review by Single-blind

Peer reviewer comments 2


Juan Churruca, Luis Vigil, Esther Luna, Julian Ruiz-Galiana, Manuel Varela

Servicio de Medicina Interna, Hospital de Móstoles, Mostoles, Madrid, Spain

Aims: In many physiologic systems, the evolution from health to disease correlates with a loss of complexity in the system’s output. We analyze the difference in complexity of the glycemic profile in healthy volunteers (H), patients with the metabolic syndrome (MS), and patients with type 2 diabetes mellitus (DM).

Methods: We measured interstitial fluid glucose every 5 minutes for 3 days in 10 H, 10 MS, and 10 DM. Complexity of the glycemic profile was evaluated by means of detrended fluctuation analysis (DFA). Mean amplitude of glycemic excursions (MAGE) was also calculated.

Results: Glucose profile was more complex (lower DFA) in healthy subjects than in patients with MS or DM (mean DFA [SD]: H: 1.25 (0.10), MS: 1.39 (0.07), DM: 1.42 (0.10). ANOVA: F2,27 = 9.94, p = 0.001). DM had also a less complex profile than MS, but this difference was not statistically significant. There was an inverse relation between complexity (lower DFA) and the number of MS defining criteria (rho = 0.55, p = 0.002) and between complexity and MAGE (r = 0.68, p < 0.0001).

Conclusions: There is a progressive loss of complexity in the glycemic profile from health, through the metabolic syndrome to type 2 diabetes mellitus. This loss of complexity precedes hyperglycemia and correlates with other markers of disease progression. Complexity analysis may be a useful tool to track the evolution from health to type 2 diabetes. Furthermore, it may provide a way to measure glycemic control in real-life situations and has some distinct advantages over other conventional variability metrics.

Keywords: complexity, metabolic syndrome, type 2 diabetes mellitus, detrended fluctuation analysis, glycemic profile

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