Glucose series complexity in hypertensive patients.
Luis Vigil1, Emilia Condés2, Manuel Varela1
1Department of Internal Medicine, University Hospital of Mostoles, Madrid, Spain.
Complexity analysis of glucose time series using detrended fluctuation analysis (DFA) shows potential for early detection of glucoregulatory dysfunction. DFA is associated with metabolic syndrome criteria and may help identify risks for type 2 diabetes development.
Area of Science:
- Physiology
- Biomedical Engineering
- Data Science
Background:
- Nonlinear methods are increasingly used for biological signal analysis.
- Complexity analysis of glucose time series may reveal early glucoregulatory dysfunction.
- Essential hypertension patients are at risk for metabolic and diabetic complications.
Purpose of the Study:
- To investigate the utility of glucose complexity analysis in patients with essential hypertension.
- To correlate glucose complexity (DFA) and variability (MAGE) with metabolic syndrome (MS) criteria.
- To identify determinants of glucose complexity in this population.
Main Methods:
- Observational, cross-sectional study of 91 essential hypertension patients.
- Glucose complexity measured by detrended fluctuation analysis (DFA).
- Glucose variability measured by mean amplitudes of glycemic excursion (MAGE).
Main Results:
- Significant correlations found between MS criteria, DFA, and MAGE.
- DFA differed significantly between patients with and without MS.
- MAGE, diastolic blood pressure, and HOMA-IR differed across DFA tertiles.
- Independent determinants of DFA were MAGE and abdominal circumference.
Conclusions:
- DFA is associated with MS and its defining criteria in hypertensive patients.
- Complexity analysis of glucose time series can detect differences related to type 2 diabetes risk.
- DFA may serve as a valuable tool in assessing glucoregulatory health.
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