Carbohydrate metabolism in children: (1) Blood sugar, serum insulin, and growth hormone during oral glucose tolerance tests; (2) Blood sugar during the cortisone glucose tolerance test

Metabolism ◽  
1973 ◽  
Vol 22 (2) ◽  
pp. 289-293 ◽  
Author(s):  
Harold S. Cole
2001 ◽  
Vol 01 (02) ◽  
pp. 193-223 ◽  
Author(s):  
SARMA S. DITTAKAVI ◽  
DHANJOO N. GHISTA

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.


Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 2158-2158
Author(s):  
Mohamed A. Yassin ◽  
Ahmed M Elawa ◽  
Ashraf T Soliman

Abstract Abstract 2158 Introduction: Both insulin deficiency and insulin resistance are reported in patients with β thalassemia major (BTM). The use of continuous blood glucose monitoring system (CGMS) among the different methods for early detection of glycaemic abnormalities has not been studied thoroughly in these patients. Aims: The aims of this study were: 1. to detect glycaemic abnormalities, if any, in young adults with BTM using fasting blood glucose (FBG), oral glucose tolerance test (OGTT), 72-h continuous glucose concentration by CGMS system, and serum insulin and C-peptide concentrations 2. To compare the results of these two methods in detecting glycaemic abnormalities in these patients and 3. To calculate homeostatic model assessment (HOMA), and the quantitative insulin sensitivity check index (QUICKI) in these patients. In order to evaluate whether glycaemic abnormalities are due to insulin deficiency and/or resistance. Materials and methods: Randomly selected young adults (n = 14) with BTM were the subjects of this study. All patients were investigated using a standard oral glucose tolerance test (OGTT) (using 75 gram of glucose) and 72-h continuous glucose concentration by CGM system (Medtronic system). Fasting serum insulin and C-peptide concentrations were measured and HOMA-B, HOMA-IR were calculated accordingly. Results: Using OGTT, 5 patients had impaired fasting glucose (IFG) (Fasting BG from 5.6 to 6.9 mmol/L). Two of them had impaired glucose tolerance IGT (BG from 7.8 and < 11.1 mmol/L) and one had BG = 16.2 mmol/L after 2-hrs (diabetic). Using CGMS in addition to the glucose data measured by glucometer (3–5 times/ day), 6 patients had IFG. The maximum (postprandial) BG recorded exceeded 11.1 mmol/L in 4 patients (28.5%) (Diabetics) and was > 7.8 but < 11.1 mmol/L in 8 patients (57%) (IGT). The mean values of HOMA and QUICKI in patients with BTM were < 2.6 (1.6± 0.8) and > 0.33 (0.36±0.03) respectively ruling out significant insulin resistance in these adolescents. There was a significant negative correlation between the β-cell function (B %) on the one hand and the fasting and the 2-h BG (r= −0.6, and − 0.48, P< 0.01 respectively) on the other hand. Serum insulin concentrations were not correlated with fasting BG or ferritin levels. The average and maximum BG levels recorded by CGMS were significantly correlated with the fasting BG (r= 0.69 and 0.6 respectively with P < 0.01) and with the BG at 2-hour after oral glucose intake (r= 0.87and 0.86 respectively with P < 0.01). Ferritin concentrations were positively correlated with the fasting BG and the 2-h BG levels in the OGTT (r= 0.69, 0.43 respectively, P < 0.001) as well as with the average and the maximum BG recorded by CGM (r =0.75, and 0.64 respectively with P < 0.01). Ferritin concentrations were negatively correlated with the β-cell function (r= −0.41, P< 0.01). Conclusion: CGMS has proved to be superior to OGTT for the diagnosis of glycaemic abnormalities in young adult patients with BTM. In our patients, defective β-cell function rather than insulin resistance appeared to be the cause for these abnormalities. The significant correlations between serum ferritin concentrations and the beta cell functions suggested the importance of adequate chelation to prevent β-cell dysfunction Disclosures: No relevant conflicts of interest to declare.


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