View clinical trials related to Diabetes Mellitus, Type 2.
Filter by:This study compares the effect on blood sugar levels of two medicines: insulin degludec and insulin glargine in people with type 2 diabetes. Participants will be treated with insulin degludec and insulin glargine during two different periods. Which treatment participants get first is decided by chance. Both medicines are approved for use in humans and available on the market. They can already be prescribed by participants' doctors. Participants will get pre-filled insulin pens to inject these insulins with. The study will last for about 41 weeks. Participants will visit the clinic 13 times and have 27 phone calls with the study doctor or study staff. At 12 of the clinic visits they will take blood samples. In order to evaluate the changes in participants' blood sugar level over time, participants will be asked to wear a small (35 millimetres (mm) x 5 mm) sensor on the back of participants' upper arm 3 times during the study. Each time participants must wear the sensor for 2 weeks. This sensor is called FreeStyle Libre Pro®. It has a very small tip which is 0.4 mm thick and is inserted 5 mm under participants' skin. Please note that participants will not be able to see the sensor readings while wearing it. The study doctor will show participants the readings when participants return to the clinic. Participants will be asked to fill in a diary in between visits. Participants will have contact with the study doctor or study staff each week. This is to adjust the dose of participants' study medicines and to ensure that participants are well. Women cannot take part if pregnant, breast-feeding or plan to become pregnant during the study period.
A Randomized,Two-period, Crossover Study to Determine the Possibility of Drug-drug Interaction After Co-administration of Metformin and Daclatasvir Where Twenty Eligible Adult Subjects Will be Randomized to Receive Either Metformin Only and/or Metformin Co-administered With Daclatasvir to measure primary outcomes including pharmacokinetics parameters as: Maximum drug concentration in plasma(Cmax), Area under the Plasma concentration Versus Time Curve from time 0 to 12 hours(AUC0-12), Clearance(CL)
This project proposes a longitudinal design that uses multinuclear-MRI to evaluate the mechanistic effects of exercise on skeletal muscle function and peripheral nerve integrity in patients with diabetic peripheral neuropathy (DPN), and to determine whether exercise can reverse DPN symptoms. The investigators will prescribe a 10-week exercise program to 40 DPN patients. The investigators will acquire multinuclear-MRI data before and after the intervention that can provide mechanistic insight into the adaptations in lower leg muscle function and peripheral nerve integrity of patients with DPN, and their role in improving DPN symptoms following physical exercise intervention.
study the prevalence of type II diabetes mellitus, prevalence of newly diagnosed type II diabetic patients
This is a cross-over study to evaluate if insulin infusion sets can be used up to 7 days.
This study aims to compare the effect of flash glucose monitoring (FGM) with traditional self-monitoring of blood glucose (SMBG) with or without carbohydrate counting and automated bolus calculation, in patients with type 1 diabetes and poor metabolic control. The investigators will include in total 200 patients recruited from 5 clinical sites in the Capital Region of Copenhagen. The patients will be randomized into four groups; A) Standard diabetes training, i.e. group training in in general diabetes health issues, B) Group training in carbohydrate counting and automated bolus calculation, the app MySugr will be taught and downloaded, C) Group training as in group A, and instructed to use FGM, D) Group training as in group B, and besides training in the use of the app MySugr, also instructed to use FGM. All patients are followed for 26 weeks with 6 clinical visits, group training (1 visit) and 2 telephone consultations. The primary outcome is time spent in normoglycemia.
The primary aim of this study is to test whether type 2 diabetes interacts with estradiol on brain metabolism in vivo in humans. This will be accomplished by imaging brain metabolism using positron emission tomography before and after short-term administration of transdermal 17β-estradiol in 10 postmenopausal women with diabetes and 10 non-diabetic postmenopausal women.
ABSTRACT Introduction: There is no current data about the effects of non-nutritive sweeteners (NNS) about important factors, such as the energy intake, appetite and its relationship in people with diabetes when tasting sweet. It is highly relevant to compare the effects of NNS intake, such as, stevia (steviol glycosides) and sucralose, previous to a mixed food on glycemic response, insulin and plasmatic concentrations of Glucagon-like peptide type 1 (GLP-1) and ghrelin in subjects with type 2 diabetes mellitus (T2DM). Objective: To compare the effects of non-nutritive sweeteners intake: stevia (steviol glyco-sides) and sucralose previous to mixed food on appetite, glycemia, insulin, ghrelin,incretin plasmatic concentrations GLP-1 in people with T2DM. Methods: Seventeen subjects with T2DM were studied in 3 different moments and they received 3 treatments: pre-load of water or sucralose or stevia and then offered to consume mixed food as a test, which provided 332 Kcal and 75 grams of available carbohydrates. Blood samples were obtained to measure the dependent variables, glycemic and insulin at times -10, 0, 30, 60, 90, 120, 150 and 180 minutes and GLP-1 with ghrelin, at times -10, 0, 30, 90, and 180 minutes. The analogue visual scale questionnaires (VAS) was conducted every 30 minutes in order to obtain the results of the depend variables: appetite and wish of specific type of food in a subjective way; appetite, satiety, relax, wish to eat any food, craving for something sweet, craving for something salty, something tasty, something fatty. Through food provided ad libi-tum (objective appetite), were obtained the results of: energy, carbohydrates, proteins and lipid intakes. The statistical analysis applied included the Shapiro-Wilk's Normality test, repeated measures ANOVA to assess differences among treatments, Friedman's test followed by Wilcoxon test corrected by Bonferroni as needed. The degree of association between variables was conducted using the Pearson's or Spearman's correlation coefficient tests, as requested. A probability value p <0.05 was considered significant.
This study is related to the development of a new model of Group Care for patients with Diabetes - the CrewD Program, incorporating close reading and creative writing in group education. A randomized trial was designed to evaluate this intervention.
Mindsets play an important role in motivating and shaping health behavior and outcomes. For example, when patients have the mindset that a treatment will work, they are more likely to adhere to treatment medications and the treatment itself becomes more effective as a result of this mindset. Providers have an opportunity to shape important patient mindsets as part of clinical care, and these mindsets may influence patients' adherence to medication, screening and vaccination recommendations, and diet, exercise, and treatment recommendations that can help patients manage chronic illness. To help care teams capitalize on the potential of leveraging mindsets in medicine and improve patient health behavior and outcomes, we developed and implemented the Medicine Plus Mindset Training as part of Primary Care 2.0. Built on more than two decades of research, this training program (a) Informs Primary Care teams about the power of patient mindsets in shaping treatment outcomes (b) Provides care teams with a language and framework to identify which patient mindsets may be at play (i.e. patient mindsets about illness, treatment, their body, and the provider/care team) and (c) Equips care teams with skills and techniques to effectively shape patient mindsets to improve health outcomes. By motivating care teams to recognize patient mindsets that may be hindering health behavior change (such as "this illness is a catastrophe") or medication adherence (such as "this medication is going to cause side effects"), care teams become better equipped to help their patients adopt more useful mindsets (such as "this treatment will work," "this illness is manageable," "my body is capable," and "I am in good hands").