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454 active trials for Diabetes Mellitus - Type 2

HbA1c Variability in Type II Diabetes

There are numerous possible reasons why it could be speculated that HbA1c variability may affect complication risk. Of interest are the concepts that both laboratory and clinic evidence suggests that periods of sustained hyperglycemia are 'remembered' (metabolic memory), this in turn is recognized to place patients at greater long-term risk of complications. As such it can be speculated that the detrimental effect of variability in HbA1c may be mediated via the same mechanism as 'metabolic memory' phenomenon. Aims: To determine whether treatment to one of 2 threshold levels will result in one group of type 2 diabetes patients having the same mean HbA1c but with differing HbA1c variability to that of another and related to markers of oxidative stress, inflammation and microvascular complications. To determine whether a difference in HbA1c variability between the 2 groups will reflect in changes in small nerve fibers assessed with the sensitive method of corneal confocal microscopy and cardiac autonomic function testing. To assess the reproducibility of HbA1c measurement from a whole blood samples initially analyzed and then stored at -80C until the end of the study (2-3 years), as well as storing an aliquot of haemolysate, for reanalysis at the end of the study. In one arm the investigators will intensify treatment in those with FPG>140mg/dl until their FPG is <90mg/dl, using whatever treatment is clinically appropriate for them, and only intensify it further if their FPG rises to >140mg/dl again. In the other group the investigators will intensify if their FPG is >115 mg/dl until it is <=115 mg/dl and intensify further if >115 mg/dl again. A total of 20 visits within a time frame of 2 and half years will be performed. Visits procedures will include routine biochemistry, eGFR, lipids, fasting glucose, insulin and full blood count, HbA1c, SHBG, hsCRP. EPIC and G-PAQ questionnaires will be collected. Autonomic function testing using deep breathing heart rate variability, and a sensitive measure of small fiber neuropathy using corneal confocal microscopy and a 24 hour urine collection for urinary isoprostanes to measure oxidative stress will be performed, at baseline, 12 and 24 months.

Start: November 2016
Scripps Digital Diabetes: Cloud-Based Continuous Glucose Monitoring (CB CGM)

Individuals with diabetes in the hospital often experience poor glycemic control, which places them at greater risk for infection, neurological and cardiac complications, mortality, longer lengths of stay, readmissions, and higher healthcare costs. There are few effective interventions for monitoring hospital glucose management therefore the long-term goal of developing Cloud-Based Real-Time Glucose Evaluation and Management System is to provide an effective, real-time continuous glucose monitoring solution necessary for clinical decision-making which can be easily managed for clinical risk 24 hrs/day. The innovative intervention will enable hospital care teams to take immediate steps based on wireless transmission of glucose data from the Dexcom G6 device, sent to a Digital Dashboard, where integration with existing real-world hospital processes can provide immediate prioritization to prevent or correct impending hypoglycemia and severe hyperglycemic events. This randomized controlled trial is defined as a Phase III/IV definitive clinical trial to establish efficacy and effectiveness of this intervention. Aim 1 will assess mean differences of % time in range between intervention and Usual Care groups to find occurrence of glucose levels that are in range at 70-200mg/dL. Aim 2 will apply the same method, using % time above range of >300mg/dL (severe hyperglycemia) and % time below range <70mg/dL (hypoglycemia). Poor glycemic control in the hospital is common and given the known consequences of uncontrolled blood sugars during a hospitalization, health systems devote significant resources to developing protocols for improving glucometrics. The likely impact of this innovative research is to have an efficient, and seamless alternative for continually monitoring glucose levels in the hospital. The Digital Dashboard facilitates real-time, remote monitoring of a large volume of patients simultaneously; automatically identifies and prioritizes patients for intervention; and will detect any and all potentially dangerous hypoglycemic episodes. The work proposed pushes the limits of these challenges by providing evidence, identified by a team-based approach to glucose management in an underserved and understudied population supplementing prior data designed to improve outcomes among high-risk patients with type 2 diabetes (T2D) and related cardio metabolic conditions. The proposed intervention is flexible, sustainable, and has high dissemination potential.

Start: February 2020