title: Glucose time series complexity as a predictor of type 2 diabetes.
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.
  
  
  
  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.
  
  
  
  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, HbA1cand DFA emerged as significant factors.
  
  
  
  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.
authors.affiliation: Internal Medicine, Hospital Universitario de Mostoles, Mostoles, Spain.
authors.forename: Carmen
authors.initials: C
authors.lastname: Rodríguez de Castro
authors.affiliation: Internal Medicine, Hospital Universitario de Mostoles, Mostoles, Spain.
authors.forename: Luis
authors.initials: L
authors.lastname: Vigil
authors.affiliation: Internal Medicine, Universidad Europea de Madrid, Madrid, Spain.
authors.forename: Borja
authors.initials: B
authors.lastname: Vargas
authors.affiliation: Internal Medicine, Hospital Universitario de Mostoles, Mostoles, Spain.
authors.forename: Emilio
authors.initials: E
authors.lastname: García Delgado
authors.affiliation: Internal Medicine, Hospital Universitario de Mostoles, Mostoles, Spain.
authors.forename: Rafael
authors.initials: R
authors.lastname: García Carretero
authors.affiliation: Internal Medicine, Hospital Universitario de Mostoles, Mostoles, Spain.
authors.forename: Julián
authors.initials: J
authors.lastname: Ruiz-Galiana
authors.affiliation: Internal Medicine, Hospital Universitario de Mostoles, Mostoles, Spain.
authors.forename: Manuel
authors.initials: M
authors.lastname: Varela
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001786:Blood Glucose / Q000032:analysis*; D003924:Diabetes Mellitus, Type 2 / Q000175:diagnosis* / Q000453:epidemiology; D005260:Female; D005500:Follow-Up Studies; D006442:Glycated Hemoglobin / Q000032:analysis; D006801:Humans; D006973:Hypertension / Q000150:complications*; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D008991:Monitoring, Physiologic / Q000379:methods*; D009765:Obesity / Q000150:complications*; D015995:Prevalence; D011379:Prognosis; D012307:Risk Factors; D013030:Spain / Q000453:epidemiology
chemical_list: D001786:Blood Glucose; D006442:Glycated Hemoglobin; C517652:hemoglobin A1c protein, human
keywords: complexity; continuous glucose monitoring; detrended fluctuation analysis; type 2 diabetes