57 resultados para Diabetes typ 1


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Uncovering factors possibly leading to insufficient metabolic control in Type 1 diabetes, both on the part of the patient or the treating physician, is of considerable relevance. The present long-term study investigated the relevance of patient-related vs education-related factors for the success in achieving acceptable glycaemic control. Adolescents or young adults with Type 1 diabetes mellitus (n= 26, mean age= 22+/-2 yr, diabetes duration= 11+/-5 yr) were followed during 36+/-5 months. All patients were treated by the same diabetologist. At the beginning of the study coping behaviour, quality of life and evaluation of emotional status were assessed. Changes in HbA1c were used as a parameter of glycaemic control. At follow-up there was a significant decrease in HbA1c of 0.4% (p<0.01). However, this was not in statistically significant correlation with age, gender, aspects of quality of life or coping behaviour. Therefore, glycaemic control and/or improvement of glycaemic control in adolescents or young adults with Type 1 diabetes mellitus seems to be primarily related to other factors, eg continuous education provided in a stable setting.

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AIMS/HYPOTHESIS: To assess the use of paediatric continuous subcutaneous infusion (CSII) under real-life conditions by analysing data recorded for up to 90 days and relating them to outcome. METHODS: Pump programming data from patients aged 0-18 years treated with CSII in 30 centres from 16 European countries and Israel were recorded during routine clinical visits. HbA(1c) was measured centrally. RESULTS: A total of 1,041 patients (age: 11.8 +/- 4.2 years; diabetes duration: 6.0 +/- 3.6 years; average CSII duration: 2.0 +/- 1.3 years; HbA(1c): 8.0 +/- 1.3% [means +/- SD]) participated. Glycaemic control was better in preschool (n = 142; 7.5 +/- 0.9%) and pre-adolescent (6-11 years, n = 321; 7.7 +/- 1.0%) children than in adolescent patients (12-18 years, n = 578; 8.3 +/- 1.4%). There was a significant negative correlation between HbA(1c) and daily bolus number, but not between HbA(1c) and total daily insulin dose. The use of <6.7 daily boluses was a significant predictor of an HbA(1c) level >7.5%. The incidence of severe hypoglycaemia and ketoacidosis was 6.63 and 6.26 events per 100 patient-years, respectively. CONCLUSIONS/INTERPRETATION: This large paediatric survey of CSII shows that glycaemic targets can be frequently achieved, particularly in young children, and the incidence of acute complications is low. Adequate substitution of basal and prandial insulin is associated with a better HbA(1c).

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We assessed systemic and local muscle fuel metabolism during aerobic exercise in patients with type 1 diabetes at euglycaemia and hyperglycaemia with identical insulin levels.

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

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.