Active clinical trials for "Diabetes Mellitus"

The goal of this pilot study is to obtain preliminary data on the magnitude of the treatment effect of IVIG on the neuropathic pain and neuropathy severity associated with treatment induced neuropathy (TIND). The investigators hypothesize that immune globulin, administered intravenously (IVIG), will reduce the pain associated with treatment induced neuropathy and reduce the neuropathy severity. Treatment induced neuropathy in diabetes, is an iatrogenic complications of diabetes. The preliminary data will be used to power a larger treatment trial, and to aid the understanding of the mitigating factors in the treatment response.

Purpose: The objective of this proposal is to study the safety and efficacy of metformin added to insulin for treatment of type 2 diabetes mellitus (T2DM) among pregnant women. Participants: 950 pregnant women with type 2 diabetes complicating pregnancy from 10 U.S. clinical centers Procedures (methods): Pregnant women with T2DM between 10 weeks and 22 weeks 6 days and a singleton fetus will be randomized to double-blinded insulin/placebo versus insulin/metformin. Primary outcome is composite adverse neonatal outcome (clinically relevant hypoglycemia, birth trauma, hyperbilirubinemia, stillbirth/neonatal death). Study visits monthly at clinical visits; blood draw at 24-30 weeks, newborn anthropometric measurements at less than 72 hours of life. Maternal and infant outcomes will be chart abstracted.

Farming for Life aims to determine the health impacts of providing weekly "prescriptions" of fresh organic vegetables to adults living with or at risk of type 2 diabetes. Over 4 years, up to 400 adults diagnosed with or at high risk of developing type 2 diabetes will be engaged for 3 months each, and receive weekly doses of locally-grown organic vegetable prescriptions. The end-points for comparison will be changes in blood pressure, weight, waist circumference, glycemic control [defined as Time in Range (TIR) (70-140mg/dl)] using continuous glucose monitoring (CGM), and HbA1c levels (a measure of long-term blood glucose level control) after 3 months compared to baseline measurements. Additional assessments will be made on the impact of the organic vegetable prescriptions on food security. At an optional Visit 13, offered 6 months after Visit 1, an additional health screening will be conducted. Prevalence and risk of type 2 diabetes in the US is disproportionately high among low income and minority groups and is exasperated by high levels of food insecurity. The investigators hypothesize that improving access to fresh organic vegetables will result in measurable health outcomes for adults with type 2 diabetes and those at risk of developing the condition. This represents a promising and potentially cost-effective strategy for improving diabetes outcomes at a population level, particularly among low income, minority populations with type 2 diabetes.

The study's goal is to promote accessible and cost-effective diabetes care through electronic means. Underserved populations including rural areas do not have diabetes specialists. Previous study data has shown the effectiveness of Internet communication in lowering a patient's Hemoglobin A1C, a measure of blood sugars, closer to the target number. The investigators thus wish to test the effectiveness of diabetes care provided by virtual means, including virtual consultations, online monitoring of blood sugars, diabetes education via web-based videos, and support/advice provided through phone or email by an Endocrinologist. The goal is to test if virtual care is a viable means to extend care for diabetes to underserved populations.

Gestational diabetes (GDM) is a condition of high blood glucose (or "blood sugar") during pregnancy. GDM can cause harmful short-term and long-term health effects for mom and baby. Diet therapy is an effective way to achieve normal blood glucose for women with GDM, but the best diet is unknown. Diet strategies that improve blood glucose in GDM and that patients can follow are needed for better clinical care. In studies of non-pregnant individuals with diabetes, eating a high fat/protein breakfast as the only dietary change was enough to improve glucose control. Because highest blood glucose readings in GDM usually occur after breakfast, a high fat/protein breakfast could also improve glucose control in GDM. In this study, two dietary strategies for improving blood glucose will be compared. Ten women newly diagnosed with GDM (<30 weeks in pregnancy) will be enrolled in a 12-day cross-over controlled feeding study with a high fat/protein breakfast, which is named a 'Macro-Optimized Diet' (MOD) or standard care diet (SC). In other words, subjects will have all food provided to them, and they will consume each diet for a few days while researchers monitor their blood glucose. Most nutrition aspects of the two diets will be similar, but the MOD diet will vary the timing of eating carbohydrate, protein, and fat to achieve fewer carbs at breakfast. After the 12-day controlled feeding period, participants will continue one of the study diets (as randomized) until delivery. During this time, research team dietitians will provide personalized nutrition education to support GDM self-management. The study will evaluate whether the diet is acceptable to women with GDM and their clinic providers. Data to be collected include blood glucose data, patient and provider feedback on diet acceptability, weight gain, the number of participants who are prescribed blood glucose control medications, and infant weight. These data will be used to evaluate trends pointing to whether one diet is more effective.

Diabetes is a complex chronic illness known for its high prevalence (11.3% in the United States), significant healthcare burdens in terms of cost and management, and high mortality rate (seventh leading cause of death in the United States in 2019). Diabetes-related complications including ischemic heart disease, stroke, hyperglycemic crises, amputations, and hypoglycemia accounted for 8.25 million hospital discharges and 25.9% of emergency department visits, contributing towards the $327 billion total cost of diabetes in 2017. Proper treatment of diabetes is integral to reduce a patient's risk of developing complications; however, a number of barriers can create additional burdens for persons with diabetes. Several studies have also demonstrated reductions in hospitalizations and/or ED visits for patients enrolled in pharmacist-led collaborative practice models. While the literature as a whole clearly describes the impact of ambulatory pharmacist intervention in achieving guideline-based clinical goals (i.e., HbA1c, blood pressure), few studies have reported on adherence with guideline-driven pharmacotherapy pre- and post-pharmacist intervention, or on pharmacist impact in reducing medication burden.

Early Basal Insulin Administration in Adult Diabetic Ketoacidosis Management

Many DM and pre-DM remain undiagnosed. The aim is to develop and validate a risk prediction function to detect DM and pre-DM in Chinese adults aged 18-84 in primary care (PC). The objectives are to: Develop a risk prediction function using non-laboratory parameters to predict DM and pre-DM from the data of the HK Population Health Survey 2014/2015 Develop a risk scoring algorithm and determine the cut-off score Validate the risk prediction function and determine its sensitivity in predicting DM and pre-DM in PC Hypothesis to be tested: The prediction function developed from the Population Health Survey (PHS) 2014/2015 is valid and sensitive in PC. Design and subjects: We will develop a risk prediction function for DM and pre-DM using data of 1,857 subjects from the PHS 2014/2015. We will recruit 1014 Chinese adults aged 18-84 from PC clinics to validate the risk prediction function. Each subject will complete an assessment on the relevant risk factors and have a blood test on OGTT and HbA1c on recruitment and at 12 months. Main outcome measures: The area under the Receiver operating characteristic (ROC) curve, sensitivity and specificity of the prediction function. Data analysis and expected results: Machine learning and Logistic regressions will be used to develop the best model. ROC curve will be used to determine the cut-off score. Sensitivity and specificity will be determined by descriptive statistics. A new HK Chinese general population specific risk prediction function will enable early case finding and intervention to prevent DM and DM complications in PC.

Diabetes mellitus (DM) is one of the main risk factors for ischemic events in patients with coronary artery disease (CAD) and diabetes is a factor in several post-PCI (Percutaneous Coronary Intervention) risk scores. However, until recently, there were almost no studies performed specifically in the diabetic population of patients undergoing PCI. This study aims to describe the anti-thrombotic regimens, clinical outcomes and current diabetes medical treatment in an unselected consecutive population of patients with DM undergoing PCI.

This study will add leptin therapy to the current insulin therapy of Type 1 Diabetics with the aim of lowering the total insulin requirements and suppressing the steep fluctuations typically associated with Type 1 Diabetes.