Diabetes mellitus is a heterogeneous clinical syndrome characterized by hyperglycemia and long-term specific complications: retinopathy, neuropathy, nephropathy, and cardiomyopathy. Automatic neuropathy leads to visceral denervation producing a variety of clinical abnormalities: cardiac and respiratory dysrythaemias, gastrointestinal motility disorders, urinary bladder dysfunction and impotence. Diabetes mellitus is a leading cause of blindness; renal failure and limb amputation all over the world. The need to detect diabetic risk factors and treat organ disorders and complications associated with diabetes provides the impetus for us to develop the technology for assessment of diabetes, its etiology and severity, as well as for assessing the efficacy of pharmacological therapy. This paper concerns: (i) modelling of blood-glucose regulation and tolerance-testing, (ii) demonstrating patient-simulation of the blood-glucose regulatory models, by means of which the model parameters can be evaluated and related to physiological parameters, and (iii) elucidating how the glucose-regulatory system model's pole-zero representation and the blood glucose-insulin transfer-function can explain the blood glucose response data in intravenous and oral glucose tolerance tests. An easy-to-implement simple clinical-application method is developed to simulate the response of the blood-glucose regulatory model in diabetic patients during intravenous glucose tolerance test and to estimate the model parameters, which can then enable differential diagnosis of diabetes and its severity as well as in early detection of risk-to-diabetes. In the oral glucose-tolerance test, the role of the gut is to facilitate transport of glucose across the intestinal wall. The Michaelis-Menten equation, describing this enzyme-catalyzed reaction rate, can be employed to conclude that the intestinal glucose absorption rate into the blood-compartment from the gut during the oral glucose-tolerance test is constant, almost resembling a rectangular pulse Nevertheless, we have formulated a new rate-control model to simulate the oral glucose-tolerance test data, by means of the response-function of a second-order system of a single-compartment (consisting of the gut and the blood-glucose pool), with the oral glucose-bolus as the impulse-input. We have also demonstrated application of this rate-control model to patients undergoing oral glucose-tolerance test, to evaluate the model parameters. By categorizing the ranges of these parameters for normals and diabetics (varying from mild to severe), we can reliably apply this model and procedure clinically.
Should we do an oral glucose tolerance test in hypertensive men with normal fasting blood-glucose?
