The aim of this study was to analyze (i) ratios between pro-inflammatory cytokines interleukin 6 (IL-6), interleukin 1 (IL-1), tumour necrosis factor alpha (TNF-alpha) and anti-inflammatory cytokine interleukin 10 (IL-10) in patients with acute myocardial infarction (AMI) and stable angina pectoris (ii) as well as correlation between IL-6 and IL-10 in AMI and (iii) correlation between IL-6 and lipoproteins in AMI.The total of 71 patients were enrolled in this study, 41 of them with AMI (study group) and 30 with stable angina pectoris (control group). The concentrations of cytokines and lipoproteins were measured from blood samples. Pro-inflammatory to anti-inflammatory cytokine ratios were calculated by dividing concentrations of pro-inflammatory cytokines with IL-10. In statistical analyses we used descriptive statistics, normality tests and analysis of correlation.IL-6: IL-10 ratio is significantly higher in AMI than in stable angina (P < 0,001), TNF-alpha: IL-10 is also higher in study group but the difference is not significant. We found positive linear correlation between IL-6 and IL-10 (r =0,43; p = 0,015) and negative linear correlation between IL-6 and high density lipoprotein HDL (r = -0,47; p= 0,008) in AMI.IL-6: IL-10 ratio is higher in AMI than in stable angina. There is linear correlation between IL-6 and IL-10 and IL-6 and HDL in AMI.

We aimed to evaluate levels of amino-terminal pro-brain natriuretic peptid (NT-proBNP) in prediction of left ventricular ejection fraction (LVEF) in heart failure patients. Prospective study on 60 consecutive patients with symptoms and signs of heart failure was performed. Blood samples for NT-proBNP analysis was taken from all test subjects and echocardiography was also done in all of them. According to LVEF value, patients were divided into four groups; those with <or=30%, 31 to 39%, 40 to 49% and >or=50%. NT-proBNP values correlated with LVEF value. Regression analysis was used to evaluate how well NT-proBNP values predict LVEF. We used Receiver Operating Characteristic Curve calculation to evaluate diagnostic performance of NT-proBNP in estimation of LVEF. Average value of NT-proBNP in test group was 3191.69+/-642.89 pg/ml (p<0.001). Average value of NT-proBNP decreased with higher LVEF categories with significant (p<0.001) and high negative correlation (r= -0,75). Stepwise multivariate linear regression analysis showed that logarithmic value of NT-proBNP was excellent predictor of LVEF value (p<0.05). Model equation based on regression analysis was LVEF=88.645-15.311 x log (NT-proBNP). Predictive model for LVEF yielded from regression analysis had sensitivities of 98% and 81%, specificities of 20% and 90%, positive predictive values of 86% and 78% and negative predictive values of 67% and 92% for predicting patients with LVEF<50% and LVEF<40%, respectively. There was negative linear correlation between NT-proBNP and LVEF. NT-proBNP was excellent predictor of LVEF value (p<0.05).