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Glucose time series complexity as a predictor of type 2 diabetes
Author(s) -
Rodríguez de Castro Carmen,
Vigil Luis,
Vargas Borja,
García Delgado Emilio,
García Carretero Rafael,
RuizGaliana Julián,
Varela Manuel
Publication year - 2017
Publication title -
diabetes/metabolism research and reviews
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.307
H-Index - 110
eISSN - 1520-7560
pISSN - 1520-7552
DOI - 10.1002/dmrr.2831
Subject(s) - quartile , diabetes mellitus , medicine , type 2 diabetes , population , detrended fluctuation analysis , multivariate analysis , proportional hazards model , endocrinology , mathematics , confidence interval , geometry , environmental health , scaling
Background 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. Methods A total of 206 patients with any of the following risk factors (1) essential hypertension, (2) obesity or (3) a first‐degree relative with a diagnosis of diabetes were included in a survival analysis study for a diagnosis of new onset type 2 diabetes. At inclusion, a glucometry by means of a Continuous Glucose Monitoring System was performed, and DFA was calculated for a 24‐h glucose time series. Patients were then followed up every 6 months, controlling for the development of diabetes. Results In a median follow‐up of 18 months, there were 18 new cases of diabetes (58.5 cases/1000 patient‐years). DFA was a significant predictor for the development of diabetes, with ten events in the highest quartile versus one in the lowest (log‐rank test chi2 = 9, df = 1, p = 0.003), even after adjusting for other relevant clinical and biochemical variables. In a Cox model, the risk of diabetes development increased 2.8 times for every 0.1 DFA units. In a multivariate analysis, only fasting glucose, HbA 1c and DFA emerged as significant factors. Conclusions Detrended fluctuation analysis significantly performed as a harbinger of type 2 diabetes development in a high‐risk population. Complexity analysis may help in targeting patients who could be candidates for intensified treatment. Copyright © 2016 The Authors. Diabetes/Metabolism Research and Reviews Published by John Wiley & Sons Ltd.