Arterial Stiffness and Complication Risk in Type 2 Diabetes

Background The prevalence and incidence of type 2 diabetes is increasing globally. A common complication of diabetes is the disease of the blood vessels, vascular diseases, which can cause disorders like myocardial infarction, stroke and kidney failure. Methods to detect early subclinical stages of macro-vascular disease are not yet available in a clinical setting. Hypothesis Arterial stiffness, an easy accessible vascular parameter, may provide additional prognostic information when evaluating risk profile for patients with diabetes type 2. Aim The aim of the project is to investigate the association between arterial stiffness and the occurrence and development of vascular complications in patients with type 2 diabetes. Specifically we want to investigate: 1. in a cross-sectional study, the association between arterial stiffness and subclinical atherosclerotic changes in the coronary arteries assessed by computed tomography (CT) and 2. in a longitudinal study, the predictive value of arterial stiffness on the development of subclinical cerebrovascular changes assessed by magnetic resonance imaging (MRI) and nephropathy assessed by urine analysis. Methods The study population consists of 100 patients with newly diagnosed type 2 diabetes and 100 age- and sex matched controls. The study participants were enrolled between 2008-2011 and extensively characterized i.a. with arterial stiffness (pulse wave velocity), MRI (white matter lesions and cerebral infarctions) and urine analysis (albuminuria). In this study we will enrol the same patients in a 5 year follow-up study in order to repeat above mentioned measurements. Furthermore, CT is used to investigate the coronary plaque burden of the participants (Agatston Score and Segment Involvement Score). Results and Perspective This project adds new insight into arterial stiffness as a predictor of the progression of micro- and macrovascular complications in patients with type 2 diabetes, and can potentially improv