View clinical trials related to Diabetes Mellitus, Type 2.
Filter by:the aim of this study was to assess serum levels of high sensitivity c reactive protein in periodontitis patients with and without type 2 diabetes in a trial to analyze its prognostic effect following non-surgical periodontal therapy.
This study compares aerobic exercise training performed before breakfast (i.e., in the fasted state) to similar training performed after breakfast in people with type 2 diabetes. Training will take place over 16 weeks.
The human ovary is the target of an autoimmune attack, usually in organ or non-specific autoimmune disorders. Serum anti-Müllerian hormone (AMH) levels decrease early in menopause and menopause is seen in women with type 1 diabetes mellitus (DM1) at a young age. DM1 is aimed to show DM1 relationship with ovarian reserve based on the assumption that it will have lower AMH levels than controls, secondary to bad glycemic control and autoimmune attack in women.
study effects of rosuvastatin on markers of atherosclerosis, thrombosis, in diabetic patients treated with glimepiride/metformin without coronary artery disease. This effect will be investigated especially on sortilin ,fetuin-A
Remote ischemic conditioning (RIC) is a therapeutic strategy for protecting organs or tissue against the detrimental effects of acute ischemia-reperfusion injury. It remains unknown whether this can be used in retinal ischemic diseases. The purpose of the present study is to examine if the autoregulation of retinal vessel diameters in diabetic patients change after remote ischemic conditioning and if the observations are different from what have been observed in normal persons.
This study aims to compare the retinal perfusion between diabetic and non-diabetic patients with Optical Coherence Tomography（OCT） Angiography after cataract surgery, to thoroughly evaluate the retinal state of diabetics after surgery, and to find out the relationship between postoperative complications occurred in retina and diabetes.
The purpose of this study is to test a way to support practices to improve attendance at retinopathy screening among people with diabetes. This new approach will be delivered to staff in general practice and involves: 1) briefing and audit training for practice staff; 2) electronic alerts on patient files to prompt GPs and nurses to remind patients, 3) face-to-face, phone and letter reminders and a brief information sheet for people with diabetes who have not attended screening, and; 4) payment to practices. The practice will carry out an audit to identify patients who have not attended screening, and re-audit at 6 months to identify any changes in attendance. The study will test this new approach over six months in eight different practices to determine whether it is feasible to deliver in a real-world setting. Four practices will be randomly assigned to receive the new approach straight away (intervention group), while the other four practices will be assigned to the group who wait, deliver care as usual, and roll out the new approach after six months (wait-list-control group). After the new approach has been tested for six months, the research team will use staff questionnaires, and carry out focus groups and interviews with patients and practice staff to learn about their experiences. The time and resources needed to deliver the approach will also be recorded to estimate the cost of delivering the new approach and how feasible it would be to carry out a larger study.
Introduction. The hemoglobin A1C (HbA1c) reflects the average blood glucose level for last two to three months. Recent advancements in the sensor technology facilitate the daily monitoring of the blood glucose using CGM devices. The future prediction of the HbA1C based on the CGM data holds a critical significance in maintaining long term health of diabetes patients. A higher than normal value of the HbA1c greatly increases the likelihood of diabetes related cardiovascular disease. Goal. The aim this study is to predict the HbA1c in advance by utilizing the CGM data through applying machine learning techniques. The outcomes of this research will assist in improving the health of diabetic patients. Methods. This is a retrospective analysis. The investigators will de-identify and analyze 120 patients with T1D who using CGM sensor for last three months. Past 15 days of CGM data will be analyzed and different glucose variability features such as time in range (TIR), coefficient of variation (CV), mean amplitude of glycemic excursion (MAGE), mean of daily differences (MODD), continuous overall net glycemic action (CONGA) will be extracted. A machine learning model will calculate (predict) HbA1c in 2-3 months advance based on these 15 days of CGM data. To evaluate the performance of the proposed prediction model, predicted HbA1c will be compared with the real HbA1c.
A randomized, double-blind, crossover trial to compare the efficacy and safety of 2 different batches of subcutaneous dasiglucagon in patients with type 1 diabetes mellitus (T1DM)
Fiasp® is a meal-time insulin that has been available in Sweden since June 2017. This study will investigate the effectiveness of Fiasp® in treating Type 1 Diabetes Mellitus. The study will be based on blood sugar measurements that the participants have uploaded to the Diasend® database and on existing data in their electronic medical records. The study does not require any additional visits to the study doctor.