View clinical trials related to Diabetes Mellitus, Type 2.
Filter by:This study aims to understand the use of continuous glucose monitors (CGM) in Asian Americans with type 2 diabetes (T2D). Researchers will compare participants on continuous glucose monitors with participants using fingerstick self-monitoring with the aim of answering the following questions: 1. Check if continuous glucose monitoring is doable and consistent for this group, and see how it affects their quality of life. 2. Estimate how well the health outcomes (glucose and lipid markers) vary over the study period. 3. Understand how social and community factors can impact the use of continuous glucose monitors in this group.
The objective of this study is to conduct a multisite trial evaluating the impact of adding an audio recording of clinic visits (AUDIO) to usual care in older adults with multimorbidity, including diabetes, compared to After Visit Summary (AVS) alone (Usual Care; UC).
Patients with type 2 diabetes who have poor blood glucose control are enrolled to evaluate the efficacy and safety of the HbA1c prediction model for adjust the hypoglycemic treatment regimen, compared with the conventional treatment using self-monitoring blood glucose or glycated albumin.
This study looks at how a person with type 2 diabetes can be treated with insulin icodec and a flash glucose monitor (a small sensor inserted under the skin to measure blood sugar all the time). The study will look at how well insulin icodec controls blood sugar when used in combination with a flash glucose monitor. Participants will get insulin icodec that they have to inject once a week on the same day of the week. The insulin will be injected with a needle in a skin fold in the thigh, upper arm, or stomach. The study will last for about 8 months. Participants will have to wear a flash glucose monitor throughout the study. This is a sensor that fits on arm. Participants will be asked to use a commercially available app called LibreView to allow team to view flash glucose monitor data. Participants will get a study phone to scan the flash glucose monitor 4 times daily and they will be able to see all of the flash glucose monitor data during the study. Women cannot take part if pregnant, breast-feeding or planning to get pregnant during the study period.
The goal of this clinical trial is to learn about the benefits of using aa Continuous Glucose Monitoring (CGM) system in patients with diabetes following discharge from the hospital. The main question it aims to answer is: • If the use of CGM with alarms is safe and effective for managing low and/or high blood sugars when compared with performing finger sticks several times per day Participants will wear one or two FreeStyle Libre CGM sensors for 12-14 days three times over a 12-week (3 month) period. This means that they will have the one to two sensors inserted under their skin. They will be asked to come to the study site four times and complete two phone calls with research staff over the 12-week period. Researchers will compare the LibreView CGM group to the Standard of Care group to see if the use of continuous glucose monitoring (CGM) reduces risk of low blood sugar in patients with type 2 diabetes (T2D) after hospital discharge when compared with the current standard method.
This pragmatic clinical trial embedded in an accountable care organization will determine the comparative effectiveness of two approaches for assigning care coordinators to older adults at risk for cardiovascular outcomes. The hypothesis is that assigning care coordinators to older adults based on perceived need will be more effective at preventing emergency department visits and hospitalizations compared to usual care.
This single-arm trial of the Diabetes Homeless Medication Support intervention for Spanish-speaking people (n=12) will test the perception and feasibility of anticipated study procedures.
Study Background: Diabetes mellitus (DM) is a major non-communicable disease. Diagnosis and self-management of DM is important. Currently, detection of diabetes requires blood tests, which is costly and inconvenient, especially for elderlies.Tongue diagnosis has been used in Chinese medicine as a routine diagnostic method, and it has recently been studied for detection of DM and diabetic retinopathy (DR). We have developed a method for taking tongue images using smartphone, which can reveal more detailed features than conventional clinical tongue inspection. There are many limitations of the preliminary study. Therefore, it is our plan in this study to address these specific limitations with the following objectives. The results of this study will enable us to develop a practical App for diabetes screening and monitoring. Study Objective The aim of the study is to develop an algorithm for diabetes screening, with the following objectives: 1. . To determine the sensitivity and specificity of tongue images taken with smartphone in predicting abnormal HbA1c (≥6.5%); 2. To determine tongue image features responsible for the classification of normal and abnormal levels of HbA1c (≥6.5%); 3. To determine the sensitivity and specificity of tongues image in predicting four different levels of HbA1c: <6% (normal), 6-6.4% (prediabetes), 6.5-8.9% (diabetes) and ≥ 9% (diabetes with high HbA1c); 4. To determine the sensitivity and specificity of combining image analysis results with the results from a TCM symptom questionnaire in predicting the four levels of HbA1c. Hypothesis: Our working hypothesis is that different tongue coating features may be associated with different stages of diabetes, as indicated by different levels of HbA1c；and different combination of symptoms from a TCM point of view may also be associated with different levels of HbA1c. Thus, combining tongue image with TCM symptoms may allow a machine learning model to build an algorithm for HbA1c prediction with reasonable accuracy. Inclusion criteria: The inclusion criteria is adult subjects with HbA1c test results from a laboratory that meets the ISO 15189 standard, such as those laboratories used by the Hospital Authority of Hong Kong. Exclusion criteria: Subjects who are unable to give consent, unable to answer the questionnaire or to cooperate in tongue image collection will be excluded. We will not include subject who are unable to understand written Chinese or English. Study design: This is a cross-sectional design looking at the relationship between tongue image pattern and HbA1c reading. Age, gender, weight, height , duration of diabetes, family history of diabetes and any comorbid disease will be recorded. The level of hemoglobin and blood lipid profile will also be recorded if the information is available. Any acute repertory or digestive illness, as well as smoking habits will also be noted. An electronic questionnaire (using Qualtrics survey software) based on published TCM symptoms of diabetes and the abovementioned information will be used for data collection. Data processing and analysis 1. Tongue segmentation The images containing the tongue and its surrounding area will be processed for segmentation of the tongue area. This segmentation is carried out by a computer algorithm developed in-house by machine learning. 2. Machine learning Two approaches will be used in machine learning. In the first approach, we will first perform image classification of either normal or abnormal HbA1c and generate the probabilities for the classification using convolutional neural networks (CNNs) (Anwar et al., 2016; Ødegaard et al., 2016). Then we will try to classify the images into four different classes according to their HbA1c level: <6% (normal), 6-6.4% (prediabetes), 6.5-8.9% (diabetes) and ≥ 9% (diabetes with high HbA1c). Primary Outcome: Tongue image features: We will extract tongue image features and perform image classification of either normal or abnormal HbA1c and generate the probabilities for the classification using convolutional neural networks (CNNs). Then we will try to classify the images into four different classes according to their HbA1c level: <6% (normal), 6-6.4% (prediabetes), 6.5-8.9% (diabetes) and ≥ 9% (diabetes with high HbA1c). Secondary Outcome: Symptom patterns: Questionnaire data will be combined with image data for regression analysis
This trial plans to learn more about the effects of a medication, semaglutide, on cardiovascular function, kidney function, and insulin sensitivity in adults with type 1 diabetes. This medication has been effective in reducing cardiovascular disease and diabetic kidney disease and improving glucose control and BMI in adults with type 2 diabetes. This study aims to look at how well the medication works in people with type 1 diabetes. Semaglutide is not approved by the FDA to be used in this way. These procedures are considered to be experimental.
Objectives: This study aimed to determine the effect of concomitant antimicrobial photodynamic therapy (aPTD) on periodontal disease and glycaemic control in patients with type 2 diabetes mellitus (T2DM). Clinical Relevance: aPTD is a noninvasive adjunctive therapy that can positively influence the periodontal treatment outcome.