Translational research : the journal of laboratory and clinical medicine
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Albuminuria is a sensitive marker to predict future cardiovascular events in patients with type 2 diabetes mellitus. However, current studies only use conventional regression models to discover predictors of albuminuria. We have used 2 different statistical models to predict albuminuria in type 2 diabetes mellitus: a multilayer perception neural network and a conditional logistic regression. ⋯ Using the conditional logistic regression model, glomerular filtration rate, time of onset to diabetes, and sex were significant indicators in the onset of albuminuria. Using a neural network model, we show that high-density lipoprotein is the most important factor in predicting albuminuria in type 2 diabetes mellitus. Our neural network model complements the current risk factor models to improve the care of patients with diabetes.
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Obesity is associated with a prothrombotic state resulting from increased thrombin generation, platelet hyper-reactivity, and decreased fibrinolysis. Data on the influence of obesity on clopidogrel-mediated platelet inhibition are conflicting and limited to platelet function tests. Moreover, there are no data on thrombin-inducible platelet activation in obese patients. ⋯ Further, high on-treatment residual ADP-inducible platelet reactivity by the VASP assay and by MEA ADP were significantly more frequent in obese patients compared with nonobese patients (both P ≤ 0.04). Finally, PAR-1 mediated platelet activation as assessed by expression of P-selectin and activated GPIIb/IIIa in response to TRAP-6 was significantly more pronounced in obese patients than in patients without obesity (both P ≤ 0.02). In conclusion, obese patients undergoing angioplasty and stenting exhibit a diminished response to clopidogrel and an increased susceptibility to TRAP-6 inducible platelet activation.