Glucose time series complexity as a predictor of type 2 diabetes.

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Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.12530/26320

Title:	Glucose time series complexity as a predictor of type 2 diabetes.
Authors:	Rodríguez-Castro, Carmen Vigil, Luis Vargas, Borja García Delgado, Emilio Garcia-Carretero, Rafael Ruiz-Galiana , Julian Varela, Manuel View more
Keywords:	complexity continuous glucose monitoring detrended fluctuation analysis type 2 diabetes View more
Mesh:	Adult Aged Aged, 80 and over Blood Glucose Diabetes Mellitus, Type 2 Female Follow-Up Studies Glycated Hemoglobin A Humans Hypertension Male Middle Aged Models, Theoretical Monitoring, Physiologic Obesity Prevalence Prognosis Risk Factors Spain View more
Issue Date:	2017
Citation:	Rodríguez de Castro C, Vigil L, Vargas B, García Delgado E, García Carretero R, Ruiz-Galiana J, et al. Glucose time series complexity as a predictor of type 2 diabetes. Diabetes Metab Res Rev. 2017 02;33(2):e2831.
Abstract:	Complexity analysis of glucose profile may provide valuable information about the gluco-regulatory system. We hypothesized that a complexity metric (detrended fluctuation analysis, DFA) may have a prognostic value for the development of type 2 diabetes in patients at risk.
PMID:	27253149
URI:	https://hdl.handle.net/20.500.12530/26320
Rights:	openAccess
Appears in Collections:	Hospitales > H. U. de Móstoles > Artículos

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