Exercise-induced growth hormone response in euglycaemia and hyperglycaemia in patients with Type 1 diabetes mellitus

To compare exercise-induced growth hormone (GH) response in patients with Type 1 diabetes during stable euglycaemic and hyperglycaemic conditions.

Response of interleukin-6 during euglycaemic and hyperglycaemic exercise in patients with type 1 diabetes mellitus

The aim of this randomized, single-blinded cross-over study was to investigate the response of interleukin-6 (IL-6) during moderate aerobic exercise in stable euglycaemia and hyperglycaemia in seven male patients with type 1 diabetes mellitus. IL-6 increased significantly over the entire study period in euglycaemia, but not in hyperglycaemia.

Pro-inflammatory biomarkers during experimental gingivitis in patients with type 1 diabetes mellitus: a proof-of-concept study

To compare gingival crevicular fluid (GCF) biomarker levels and microbial distribution in plaque biofilm (SP) samples for subjects with type 1 diabetes (T1DM) versus healthy subjects without diabetes during experimental gingivitis (EG).

Exercise capacity in subjects with type 1 diabetes mellitus in eu- and hyperglycaemia

Circumstantial evidence suggests that an increase in plasma glucose availability improves exercise capacity in subjects with type 1 diabetes mellitus. The aim of this study was to assess exercise capacity in eu- and hyperglycaemic conditions in subjects with type 1 diabetes.

Apolipoprotein B as a long-term predictor of mortality in type 1 diabetes mellitus: a 15-year follow up

To evaluate the association of apolipoprotein B (apo B) with mortality due to all causes, to cardiac disease and to ischaemic heart disease (IHD) in subjects with type 1 diabetes mellitus.

Quality of life and coping behaviour in Type 1 diabetes mellitus: relationship with metabolic control

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.

Fuel metabolism during exercise in euglycaemia and hyperglycaemia in patients with type 1 diabetes mellitus--a prospective single-blinded randomised crossover trial

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.

[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.

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.

Prevalence of vascular disease in systemic lupus erythematosus compared with type-1 diabetes mellitus: a cross-sectional study of two cohorts.

OBJECTIVES Systemic lupus erythematosus (SLE) is associated with considerable cardiovascular morbidity that has not yet been directly compared with other diseases with known cardiovascular risk. METHODS Two hundred and forty-one patients of the multicentre Swiss SLE cohort study (SSCS) were cross-sectionally assessed for coronary heart disease (CHD), cerebrovascular disease (CVD) and peripheral artery disease (PAD). SLE patients were compared with a cohort of 193 patients with type-1 diabetes mellitus being followed at the University Hospital Basel. A subgroup analysis of 50 age- and sex-matched patients from the University Hospital Basel was performed. RESULTS Of patients within the SSCS 13.3% had one or more vascular events: 8.3% CHD, 5% CVD and 1.2% PAD. In type-1 diabetes mellitus patients, 15% had vascular events: 9.3% CHD, 3.1% CVD and 5.6% PAD. In the matched subgroup, 26% of SLE patients had vascular events (14% CHD) compared with 12% in type-1 DM patients (2% CHD). Cardiovascular risk factors were similar in both groups. Vascular events in SLE patients were associated with age, longer disease duration, dyslipidaemia, and hypertension. CONCLUSION Cardiovascular morbidity in SLE is at least as frequent as in age- and sex-matched type-1 diabetes mellitus patients. Therefore, aggressive screening and management of cardiovascular risk factors should be performed.

Exercise-associated glucose metabolism in individuals with type 1 diabetes mellitus.

PURPOSE OF REVIEW The primary focus of this review is threefold: first, to summarize available knowledge on exercise-associated glucose metabolism in individuals with type 1 diabetes mellitus (T1DM); second, to elucidate physiological mechanisms predisposing to glycemic variations in patients in T1DM; and third, to describe novel approaches derived from physiological perceptions applicable to stabilize exercise-related glycemia in individuals with T1DM. RECENT FINDINGS Recent studies corroborate the concept that despite partial differences in counter-regulatory mechanisms individuals with T1DM do not fundamentally differ in their glucose response to exercise when compared with healthy individuals if studies are performed under standardized conditions with insulin and glucose levels held close to physiological ranges. Novel approaches derived from a better understanding of exercise-associated glucose metabolism (e.g., the concept of intermittent high-intensity exercise) may provide alternative ways to master the challenges imposed by exercise to individuals with T1DM. SUMMARY Exercise still imposes high demands on patients with T1DM and increases risks for hypoglycemia and hyperglycemia. Deeper insight into the associated metabolic pathways has revealed novel options to stabilize exercise-associated glucose levels in these patients.

Carbohydrate Estimation by a Mobile Phone-Based System Versus Self-Estimations of Individuals With Type 1 Diabetes Mellitus: A Comparative Study

Background: Diabetes mellitus is spreading throughout the world and diabetic individuals have been shown to often assess their food intake inaccurately; therefore, it is a matter of urgency to develop automated diet assessment tools. The recent availability of mobile phones with enhanced capabilities, together with the advances in computer vision, have permitted the development of image analysis apps for the automated assessment of meals. GoCARB is a mobile phone-based system designed to support individuals with type 1 diabetes during daily carbohydrate estimation. In a typical scenario, the user places a reference card next to the dish and acquires two images using a mobile phone. A series of computer vision modules detect the plate and automatically segment and recognize the different food items, while their 3D shape is reconstructed. Finally, the carbohydrate content is calculated by combining the volume of each food item with the nutritional information provided by the USDA Nutrient Database for Standard Reference. Objective: The main objective of this study is to assess the accuracy of the GoCARB prototype when used by individuals with type 1 diabetes and to compare it to their own performance in carbohydrate counting. In addition, the user experience and usability of the system is evaluated by questionnaires. Methods: The study was conducted at the Bern University Hospital, “Inselspital” (Bern, Switzerland) and involved 19 adult volunteers with type 1 diabetes, each participating once. Each study day, a total of six meals of broad diversity were taken from the hospital’s restaurant and presented to the participants. The food items were weighed on a standard balance and the true amount of carbohydrate was calculated from the USDA nutrient database. Participants were asked to count the carbohydrate content of each meal independently and then by using GoCARB. At the end of each session, a questionnaire was completed to assess the user’s experience with GoCARB. Results: The mean absolute error was 27.89 (SD 38.20) grams of carbohydrate for the estimation of participants, whereas the corresponding value for the GoCARB system was 12.28 (SD 9.56) grams of carbohydrate, which was a significantly better performance ( P=.001). In 75.4% (86/114) of the meals, the GoCARB automatic segmentation was successful and 85.1% (291/342) of individual food items were successfully recognized. Most participants found GoCARB easy to use. Conclusions: This study indicates that the system is able to estimate, on average, the carbohydrate content of meals with higher accuracy than individuals with type 1 diabetes can. The participants thought the app was useful and easy to use. GoCARB seems to be a well-accepted supportive mHealth tool for the assessment of served-on-a-plate meals.

SMARTDIAB: a communication and information technology approach for the intelligent monitoring, management and follow-up of type 1 diabetes patients

SMARTDIAB is a platform designed to support the monitoring, management, and treatment of patients with type 1 diabetes mellitus (T1DM), by combining state-of-the-art approaches in the fields of database (DB) technologies, communications, simulation algorithms, and data mining. SMARTDIAB consists mainly of two units: 1) the patient unit (PU); and 2) the patient management unit (PMU), which communicate with each other for data exchange. The PMU can be accessed by the PU through the internet using devices, such as PCs/laptops with direct internet access or mobile phones via a Wi-Fi/General Packet Radio Service access network. The PU consists of an insulin pump for subcutaneous insulin infusion to the patient and a continuous glucose measurement system. The aforementioned devices running a user-friendly application gather patient's related information and transmit it to the PMU. The PMU consists of a diabetes data management system (DDMS), a decision support system (DSS) that provides risk assessment for long-term diabetes complications, and an insulin infusion advisory system (IIAS), which reside on a Web server. The DDMS can be accessed from both medical personnel and patients, with appropriate security access rights and front-end interfaces. The DDMS, apart from being used for data storage/retrieval, provides also advanced tools for the intelligent processing of the patient's data, supporting the physician in decision making, regarding the patient's treatment. The IIAS is used to close the loop between the insulin pump and the continuous glucose monitoring system, by providing the pump with the appropriate insulin infusion rate in order to keep the patient's glucose levels within predefined limits. The pilot version of the SMARTDIAB has already been implemented, while the platform's evaluation in clinical environment is being in progress.