BLOOD SUGAR REGULATION AND THE ORIGIN OF THE HYPERGLYCEMIAS

Blood-Sugar Studies in Mental Disorders

It is a common experience in the investigation of mental disorders that glycosuria is frequently found, thus indicating a tendency in such cases to a faulty carbohydrate metabolism. With the exception of epilepsy, this occurrence of glycosuria has been noted in most mental conditions. Intermittent glycosuria is met with in general paralysis (Kraepelin) (1); Bond (2) and Strauss (3) note it in about 10per cent.of their cases. In dementia prócox Schultze and Knauer (4) did not observe glycosuria in the apathetic form of hebephrenia, but often found it to occur with catatonic excitement. With other observers (see Allers (5)) they record the marked association of glycosuria with depressed states, while its occurrence in mania was infrequent except in markedly excited and resistive cases.

The fractal nature of blood glucose fluctuations

AIMS

Fluctuations 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.

METHODS

We 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.

RESULTS

Glucose fluctuations extracted for prolonged time periods show fractal-like behavior and power law behavior of the system.

CONCLUSIONS

Hidden 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.