Prediabetes is a condition that requires early intervention against diabetic macrovascular complications. This study aims to assess whether or not the likelihood of diabetes macrovascular complications occurring in prediabetes can be better estimated by a model combining a set of conventional and emerging biomarkers, with a view to improving cardiovascular disease (CVD) screening in individuals with elevated blood glucose levels associated with prediabetes. A total of 71 participants (female/male: 32/39) were divided into two groups ' the prediabetic group (preDM: n=34) and the diabetic with cardiovascular complications group (DM+CVD: n=37). Blood glucose level (BGL), blood pressure (BP), total cholesterol (TC), high-density lipoprotein (HDL) and TC:HDL ratio, erythrocyte oxidative stress (as determined by reduced glutathione [GSH], malondialdehyde and methaemoglobin levels) and vascular events (D-dimer, homocysteine and whole blood viscosity) were measured. Statistical analysis was by binomial logistic regression modelling with forward likelihood ratio step procedures. A combination of BGL, BP, erythrocyte GSH and TC gave the best group identifications, with 28/34 (82.4%) and 29/37 (78.4%) members correctly identified in the preDM and DM+CVD groups, respectively. Six of the 34 (17.6%) prediabetes individuals were logistically identified as having diabetic macrovascular complications, but clinically did not qualify for CVD intervention under current screening models. The authors propose that a combination of BGL, BP, erythrocyte GSH and TC can provide a clinically acceptable standard for identifying CVD risk in individuals with prediabetes. This model provides a tool for early identification and targeted intervention in individuals with subclinical diabetes who are at risk of CVD.
|Number of pages||8|
|Journal||British Journal of Biomedical Science|
|Publication status||Published - 2010|