Correlation between Progetto Cuore risk score and early cardiovascular damage in never treated subjects

Effect of blood purification on serum miR-126 and VEGF levels in the process of atherosclerosis in uremic patients under maintenance hemodialysis

This study aims to study the influence of different blood purification approaches on the expression of miR-126 and VEGF serum levels in the development of atherosclerosis in uremic patients under maintenance hemodialysis (MHD). A total of 207 MHD patients with uremia were divided into HD (hemodialysis, n = 60), HDF (hemodiafiltration, n = 72), and HD + HP (hemodialysis + hemoperfusion, n = 75) groups based on different purification approaches. Eighty individuals who underwent physical examinations during the same period constituted the healthy controls. The serum levels of miR-126 and VEGF were examined by qRT-PCR and ELISA both before and after treatment, and the intima media thickness (IMT) value and plaque area were evaluated by color Doppler ultrasound. The serum miR-126 level was down-regulated in MHD patients compared with healthy controls, and this was negatively linked to VEGF. The post-treatment expression level of serum miR-126 in the HDF and HD + HP groups was remarkably increased, but VEGF was decreased in MHD patients, and especially significantly in the HDF group. In addition, IMT and plaque area were obviously improved in the HD group after treatment. Pearson correlation analysis showed a negative correlation of miR-126 with IMT and plaque area, but a positive association between VEGF and IMT and plaque area. miR-126 and VEGF are expected to become a valuable biomarker for monitoring the progression of atherosclerosis in uremic patients undergoing MHD.

Improving prediction algorithms for cardiometabolic risk in children and adolescents

Clustering of abnormal metabolic traits, the Metabolic Syndrome (MetS), has been associated with an increased cardiovascular disease (CVD) risk. Several algorithms including the MetS and other risk factors exist for adults to predict the risk of CVD. We discuss the use of MetS scores and algorithms in an attempt to predict later cardiometabolic risk in children and adolescents and offer suggestions for developing clinically useful algorithms in this population. There is little consensus in how to define the MetS or to predict future CVD risk using the MetS and other risk factors in children and adolescents. The MetS scores and prediction algorithms we identified had usually not been tested against a clinical outcome, such as CVD, and they had not been validated in other populations. This makes comparisons of algorithms impossible. We suggest a simple two-step approach for predicting the risk of adult cardiometabolic disease in overweight children. It may have advantages in terms of cost-effectiveness since it uses simple measurements in the first step and more complex, costly measurements in the second step. It also takes advantage of the continuous distributions of the metabolic features. We suggest piloting and validating any new algorithms.