Glycemic control and macrovascular disease in types 1 and 2 diabetes mellitus: Meta-analysis of randomized trials

Uncertainty persists concerning the effect of improved long-term glycemic control on macrovascular disease in diabetes mellitus (DM).

Long-term cardiovascular and non-cardiovascular mortality in women and men with type 1 and type 2 diabetes mellitus: a 30-year follow-up in Switzerland

While studies from other countries have shown an excess mortality in diabetic individuals when compared with the general population, comparable long-term data is not available for Switzerland.

[Role of complementary medicine in type 1 diabetes mellitus in two Swiss centres]

Insulin replacement is the only effective treatment of type 1 Diabetes mellitus (T1DM). Nevertheless, many complementary treatments are in use for T1DM. In this study we assessed by questionnaire that out of 342 patients with T1DM, 48 (14%; 13.4% adult, 18.5% paediatric; 20 male, 28 female) used complementary medicine (CM) in addition to their insulin therapy. The purpose of the use of CM was to improve general well-being, ameliorate glucose homeostasis, reduce blood glucose levels as well as insulin doses, improve physical fitness, reduce the frequency of hypoglycaemia, and control appetite. The modalities most frequently used are cinnamon, homeopathy, magnesium and special beverages (mainly teas). Thus, good collaboration between health care professionals will allow optimal patient care.

A reduction in severe hypoglycaemia in type 1 diabetes in a randomized crossover study of continuous intraperitoneal compared with subcutaneous insulin infusion

Continuous intraperitoneal insulin infusion (CIPII) with the DiaPort system using regular insulin was compared to continuous subcutaneous insulin infusion (CSII) using insulin Lispro, to investigate the frequency of hypoglycemia, blood glucose control, quality of life, and safety.

The effect of growth hormone (GH) replacement therapy in adult patients with type 1 diabetes mellitus and GH deficiency

Specific problems in patients with insulin-dependent diabetes mellitus (IDDM) and GH deficiency are hypoglycaemic attacks, increased insulin sensitivity and loss of energy. These problems may be related to GH deficiency.

Effect of IGF-I therapy on VLDL apolipoprotein B100 metabolism in type 1 diabetes mellitus

Abnormal lipid metabolism may be related to the increased cardiovascular risk in type 1 diabetes. Secretion and clearance rates of very low density lipoprotein (VLDL) apolipoprotein B100 (apoB) determine plasma lipid concentrations. Type 1 diabetes is characterized by increased growth hormone (GH) secretion and decreased insulin-like growth factor (IGF) I concentrations. High-dose IGF-I therapy improves the lipid profile in type 1 diabetes. This study examined the effect of low-dose (40 microg.kg(-1).day(-1)) IGF-I therapy on VLDL apoB metabolism, VLDL composition, and the GH-IGF-I axis during euglycemia in type 1 diabetes. Using a stable isotope technique, VLDL apoB kinetics were estimated before and after 1 wk of IGF-I therapy in 12 patients with type 1 diabetes in a double-blind, placebo-controlled trial. Fasting plasma triglyceride (P < 0.03), VLDL-triglyceride concentrations (P < 0.05), and the VLDL-triglyceride-to-VLDL apoB ratio (P < 0.002) significantly decreased after IGF-I therapy, whereas VLDL apoB kinetics were not significantly affected by IGF-I therapy. IGF-I therapy resulted in a significant increase in IGF-I and a significant reduction in GH concentrations. The mean overnight insulin concentrations during euglycemia decreased by 25% after IGF-I therapy. These results indicate that low-dose IGF-I therapy restores the GH-IGF-I axis in type 1 diabetes. IGF-I therapy changes fasting triglyceride concentrations and VLDL composition probably because of an increase in insulin sensitivity.

Normal VLDL metabolism despite altered lipoprotein composition in type 1 diabetes mellitus

Patients with type 1 diabetes are at increased risk of cardiovascular disease, which may be related to abnormal lipid metabolism. Secretion and clearance of VLDL apolipoprotein B100 (apoB) are important determinants of plasma lipid concentrations and are known to be influenced by hormones, including insulin and growth hormone.

IGF-I treatment in adults with type 1 diabetes: effects on glucose and protein metabolism in the fasting state and during a hyperinsulinemic-euglycemic amino acid clamp

Type 1 diabetes is associated with abnormalities of the growth hormone (GH)-IGF-I axis. Such abnormalities include decreased circulating levels of IGF-I. We studied the effects of IGF-I therapy (40 microg x kg(-1) x day(-1)) on protein and glucose metabolism in adults with type 1 diabetes in a randomized placebo-controlled trial. A total of 12 subjects participated, and each subject was studied at baseline and after 7 days of treatment, both in the fasting state and during a hyperinsulinemic-euglycemic amino acid clamp. Protein and glucose metabolism were assessed using infusions of [1-13C]leucine and [6-6-2H2]glucose. IGF-I administration resulted in a 51% rise in circulating IGF-I levels (P < 0.005) and a 56% decrease in the mean overnight GH concentration (P < 0.05). After IGF-I treatment, a decrease in the overnight insulin requirement (0.26+/-0.07 vs. 0.17+/-0.06 U/kg, P < 0.05) and an increase in the glucose infusion requirement were observed during the hyperinsulinemic clamp (approximately 67%, P < 0.05). Basal glucose kinetics were unchanged, but an increase in insulin-stimulated peripheral glucose disposal was observed after IGF-I therapy (37+/-6 vs. 52+/-10 micromol x kg(-1) x min(-1), P < 0.05). IGF-I administration increased the basal metabolic clearance rate for leucine (approximately 28%, P < 0.05) and resulted in a net increase in leucine balance, both in the basal state and during the hyperinsulinemic amino acid clamp (-0.17+/-0.03 vs. -0.10+/-0.02, P < 0.01, and 0.25+/-0.08 vs. 0.40+/-0.06, P < 0.05, respectively). No changes in these variables were recorded in the subjects after administration of placebo. These findings demonstrated that IGF-I replacement resulted in significant alterations in glucose and protein metabolism in the basal and insulin-stimulated states. These effects were associated with increased insulin sensitivity, and they underline the major role of IGF-I in protein and glucose metabolism in type 1 diabetes.

An insulin infusion advisory system for type 1 diabetes patients based on non-linear model predictive control methods

In this paper, an Insulin Infusion Advisory System (IIAS) for Type 1 diabetes patients, which use insulin pumps for the Continuous Subcutaneous Insulin Infusion (CSII) is presented. The purpose of the system is to estimate the appropriate insulin infusion rates. The system is based on a Non-Linear Model Predictive Controller (NMPC) which uses a hybrid model. The model comprises a Compartmental Model (CM), which simulates the absorption of the glucose to the blood due to meal intakes, and a Neural Network (NN), which simulates the glucose-insulin kinetics. The NN is a Recurrent NN (RNN) trained with the Real Time Recurrent Learning (RTRL) algorithm. The output of the model consists of short term glucose predictions and provides input to the NMPC, in order for the latter to estimate the optimum insulin infusion rates. For the development and the evaluation of the IIAS, data generated from a Mathematical Model (MM) of a Type 1 diabetes patient have been used. The proposed control strategy is evaluated at multiple meal disturbances, various noise levels and additional time delays. The results indicate that the implemented IIAS is capable of handling multiple meals, which correspond to realistic meal profiles, large noise levels and time delays.

A communication and information technology infrastructure for real time monitoring and management of type 1 diabetes patients

This paper is focused on the integration of state-of-the-art technologies in the fields of telecommunications, simulation algorithms, and data mining in order to develop a Type 1 diabetes patient's semi to fully-automated monitoring and management system. The main components of the system are a glucose measurement device, an insulin delivery system (insulin injection or insulin pumps), a mobile phone for the GPRS network, and a PDA or laptop for the Internet. In the medical environment, appropriate infrastructure for storage, analysis and visualizing of patients' data has been implemented to facilitate treatment design by health care experts.

Neural network based glucose - insulin metabolism models for children with Type 1 diabetes

In this paper two models for the simulation of glucose-insulin metabolism of children with Type 1 diabetes are presented. The models are based on the combined use of Compartmental Models (CMs) and artificial Neural Networks (NNs). Data from children with Type 1 diabetes, stored in a database, have been used as input to the models. The data are taken from four children with Type 1 diabetes and contain information about glucose levels taken from continuous glucose monitoring system, insulin intake and food intake, along with corresponding time. The influences of taken insulin on plasma insulin concentration, as well as the effect of food intake on glucose input into the blood from the gut, are estimated from the CMs. The outputs of CMs, along with previous glucose measurements, are fed to a NN, which provides short-term prediction of glucose values. For comparative reasons two different NN architectures have been tested: a Feed-Forward NN (FFNN) trained with the back-propagation algorithm with adaptive learning rate and momentum, and a Recurrent NN (RNN), trained with the Real Time Recurrent Learning (RTRL) algorithm. The results indicate that the best prediction performance can be achieved by the use of RNN.

A Communication Platform for Tele-monitoring and Tele-management of Type 1 Diabetes

Type 1 diabetes mellitus is a chronic disease characterized by blood glucose levels out of normal range due to inability of insulin production. This dysfunction leads to many short- and long-term complications. In this paper, a system for tele-monitoring and tele-management of Type 1 diabetes patients is proposed, aiming at reducing the risk of diabetes complications and improving quality of life. The system integrates Wireless Personal Area Networks (WPAN), mobile infrastructure, and Internet technology along with commercially available and novel glucose measurement devices, advanced modeling techniques, and tools for the intelligent processing of the available diabetes patients information. The integration of the above technologies enables intensive monitoring of blood glucose levels, treatment optimisation, continuous medical care, and improvement of quality of life for Type 1 diabetes patients, without restrictions in everyday life activities.

A real time simulation model of glucose-insulin metabolism for type 1 diabetes patients

In this paper, a simulation model of glucose-insulin metabolism for Type 1 diabetes patients is presented. The proposed system is based on the combination of Compartmental Models (CMs) and artificial Neural Networks (NNs). This model aims at the development of an accurate system, in order to assist Type 1 diabetes patients to handle their blood glucose profile and recognize dangerous metabolic states. Data from a Type 1 diabetes patient, stored in a database, have been used as input to the hybrid system. The data contain information about measured blood glucose levels, insulin intake, and description of food intake, along with the corresponding time. The data are passed to three separate CMs, which produce estimations about (i) the effect of Short Acting (SA) insulin intake on blood insulin concentration, (ii) the effect of Intermediate Acting (IA) insulin intake on blood insulin concentration, and (iii) the effect of carbohydrate intake on blood glucose absorption from the gut. The outputs of the three CMs are passed to a Recurrent NN (RNN) in order to predict subsequent blood glucose levels. The RNN is trained with the Real Time Recurrent Learning (RTRL) algorithm. The resulted blood glucose predictions are promising for the use of the proposed model for blood glucose level estimation for Type 1 diabetes patients.

A neural network approach for insulin regime and dose adjustment in type 1 diabetes

A decision support system based on a neural network approach is proposed to advise on insulin regime and dose adjustment for type 1 diabetes patients.

Circadian blood pressure during the early course of type 1 diabetes. Analysis of 1,011 ambulatory blood pressure recordings in 354 adolescents and young adults

OBJECTIVE Little information is available on the early course of hypertension in type 1 diabetes. The aim of our study, therefore, was to document circadian blood pressure profiles in patients with a diabetes duration of up to 20 years and relate daytime and nighttime blood pressure to duration of diabetes, BMI, insulin therapy, and HbA1c. RESEARCH DESIGN AND METHODS Ambulatory profiles of 24-h blood pressure were recorded in 354 pediatric patients with type 1 diabetes (age 14.6 +/- 4.2 years, duration of diabetes 5.6 +/- 5.0 years, follow-up for up to 9 years). A total of 1,011 profiles were available for analysis from patients not receiving antihypertensive medication. RESULTS Although daytime mean systolic pressure was significantly elevated in diabetic subjects (+3.1 mmHg; P < 0.0001), daytime diastolic pressure was not different from from the height- and sex-adjusted normal range (+0.1 mmHg, NS). In contrast, both systolic and diastolic nighttime values were clearly elevated (+7.2 and +4.2 mmHg; P < 0.0001), and nocturnal dipping was reduced (P < 0.0001). Systolic blood pressure was related to overweight in all patients, while diastolic blood pressure was related to metabolic control in young adults. Blood pressure variability was significantly lower in girls compared with boys (P < 0.01). During follow-up, no increase of blood pressure was noted; however, diastolic nocturnal dipping decreased significantly (P < 0.03). Mean daytime blood pressure was significantly related to office blood pressure (r = +0.54 for systolic and r = +0.40 for diastolic pressure); however, hypertension was confirmed by ambulatory blood pressure measurement in only 32% of patients with elevated office blood pressure. CONCLUSIONS During the early course of type 1 diabetes, daytime blood pressure is higher compared with that of healthy control subjects. The elevation of nocturnal values is even more pronounced and nocturnal dipping is reduced. The frequency of white-coat hypertension is high among adolescents with diabetes, and ambulatory blood pressure monitoring avoids unnecessary antihypertensive treatment.