The fractal nature of blood glucose fluctuations

Abstract

AimsFluctuations of blood glucose are generated by multiple external and internal factors continuously modifying glucose concentrations through complex feedback loops. This equilibrium may be perturbed during physiological or pathological conditions. The traditional theory suggests that physiological systems achieve homeostasis when disturbed and restore equilibrium through linear feedback loops. Complex systems on the other hand, may function nonlinearly with feedback loops that operate at different time scales, exhibiting chaotic or fractal behavior. We hypothesized that blood glucose fluctuations recorded for prolonged time periods show chaotic, fractal-like behavior that may be altered in diabetes. MethodsWe applied nonlinear analytical methods such as detrended fluctuation analysis to glucose data derived from continuous glucose monitoring devices for prolonged time periods in healthy volunteers, diabetes type 1 and pregnant diabetes type 1 patients. ResultsGlucose fluctuations extracted for prolonged time periods show fractal-like behavior and power law behavior of the system. ConclusionsHidden features underlying glucose fluctuations in health and in disease were revealed by using dynamic nonlinear analyses methods to discrete glucose readings extracted from continuous glucose monitoring devices. By using such methods we can enhance our understanding of the dynamics of blood glucose fluctuations in health and disease.