View clinical trials related to CGM.
Filter by:In the framework of PhD research, the investigators will present a visualization of estimation of CVDs risk and the possibility of monitoring blood glucose levels in real-time. Based on the results, the investigators will assess the association of these with lifestyle change. The findings highlight the need for sufficiently reliable and high-quality evaluations of visualizations, technologies or applications used in the family medicine.
Real-time continuous glucose monitoring (CGM) systems provide users with information about current glucose levels and alert the patient before the upper or lower glucose threshold is reached or when glucose levels change rapidly. Hence, glycaemic excursions can be early identified and accordingly adapted by behavioural change or pharmacologic intervention. Randomized controlled studies adequately powered to evaluate the impact of long-term application of real-time CGM systems on the risk reduction of adverse obstetric outcomes are missing.
The goal of this study is to assess the impact of physician-driven insulin setting changes in type 1 patients using multiple daily injection insulin therapy with exercise. This is a short outpatient study with multiple outpatient and home exercise sessions with an assigned type of exercise.
In a previous study we used the FreeStyle Navigator Continuous Glucose Monitoring (CGM) System to obtain 30 days of glucose measurements from 30 people with diabetes treated with insulin. The purpose of this study is to characterize glycemia (glucose) control in 30 people without diabetes and to compare these data to the 30 people with diabetes from a previous study. Through this approach it may be possible to develop a means of establishing a model of normal glucose patterns and a basis of comparison with glucose patterns in people with diabetes.
The purpose of this study is to obtain sufficient continuous glucose monitoring (CGM) data in a manner that provides clinical information that is not available using conventional self-monitored blood glucose. Currently, a formal method does not exist for evaluating CGM data except for looking at each glucose reading across the days a CGM system has been worn and evaluating it based on clinical practice experience. The hope is that a mathematical model can be developed that will enable health care providers to quickly and easily determine what changes in diabetes treatment need to be made after CGM data is obtained.