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In populations with high prevalences of diabetes and obesity, estimating glomerular filtration rate (GFR) by using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation may predict cardiovascular disease (CVD) risk better than by using the Modification of Diet in Renal Disease (MDRD) Study equation.
Although WBC is in normal range, subtypes of WBC like N/L ratio may predict cardiovascular mortality.
In patients with CKD, excess circulating sVEGFR-1 levels were associated with endothelial dysfunction, suggesting that increased sVEGFR-1 levels may predict cardiovascular risk in CKD [ 116].
Other markers of inflammation that may predict cardiovascular disease are soluble forms of intercellular adhesion molecule-1 (sICAM-1) and vascular cell adhesion molecule-1 (sVCAM-1) [ 18], which are interrelated markers of inflammation and endothelial function.
Elevated plasma levels of asymmetric dimethylarginine (ADMA) has been reported to be associated with insulin resistance and micro/macrovascular diabetic complications, and may predict cardiovascular events in type 2 diabetic patients.
It has been reported that elevated plasma levels of ADMA are associated with insulin resistance, micro/macrovascular diabetic complications, and may predict cardiovascular events in type 2 diabetic patients.
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Narrowed retinal arterioles may independently predict cardiovascular disease.
Maximum net ST segment deviation and DTS may predict suspected cardiovascular disease (CVD).
These two studies suggest that HDL structure and function may predict atherosclerotic cardiovascular disease better than HDL-cholesterol levels.
Moreover, several prospective studies have demonstrated that elevated plasma ADMA level may predict adverse cardiovascular events in type 2 diabetic patients [ 13, 14].
Noninvasive assessments of peripheral endothelial function in the microcirculation and the macrocirculation may predict adverse cardiovascular outcomes in patients at risk of developing, or with prevalent CVD [ 4].
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