Oral antiplatelet drugs are a cornerstone of modern pharmacotherapy in cardiovascular atherothrombotic diseases. The efficacy of acetylsalicylic acid (ASA, aspirin) and clopidogrel in decreasing the risk of adverse events in coronary heart disease patients has been well established in the past 20 years. Despite chronic oral antiplatelet therapy, a number of atherothombotic events continue to occur. In recent years, a number of reports in the literature have shown possible relationships between residual platelet activity, as measured with a variety of laboratory tests, and clinical outcome, raising the possibility that ‘resistance’ to oral antiplatelet drugs may underlie many such clinical adverse events. The present position paper, conveyed within a group of clinical cardiologists with expertise in thrombosis appointed by the Section of Cardiovascular Interventions of the Polish Cardiac Society, has been further elaborated and endorsed by the Working Group on Thrombosis of the European Society of Cardiology. It aims at summarizing the main findings in this complex area, issuing opinions in cases of high controversy, and fostering future research in this area to obtain reliable laboratory and clinical data for the resolution of the many problems still open.

Summary: The objective was to describe the indices of platelet aggregation and activation in a large cohort of diabetic patients with coronary artery disease (CAD). Recently, a number of observations have indicated that patients with diabetes mellitus (DM) exhibit persistent platelet activation, and low response after antiplatelet therapy, although no randomized data exist. We sought to define the baseline platelet biomarkers, and the patterns of response to aspirin and clopidogrel therapy in DM versus non-diabetic patients. Secondary post-hoc analyses were made of platelet activity biomarkers in the dataset which consisted of patients with documented CAD (n=822), including those with DM (n=257). Patients with DM exhibited higher baseline platelet activity by adenosine diphosphate (ADP)- (p=0.0002), and collagen-induced (p=0.03) aggregometry; Ultegra- (p=0.0001), and PFA-100 (p=0.02) analyzers; and expression of platelet/endothelial cell adhesion molecule-1 (PECAM-1) (p=0.01), glycoprotein (GP) IIb/IIIa antigen (p=0.001), and activity (p=0.02), vitronectin receptor (p=0.03), P selectin (p=0.02), and intact epitope of PAR-1 thrombin receptor (p=0.02). Antiplatelet response after clopidogrel in diabetics was impaired when compared with non-diabetics. In conclusion, diabetic patients exhibit high pretreatment platelet activity, and do not respond well to the available antiplatelet regimens when compared with similar patients without DM. The clinical implications of these findings are unknown but are potentially important. Considering worsened outcomes in this high-risk population, clinical trials in DM are urgently needed in order to define the optimal degree of platelet inhibition and suitability for more aggressive antiplatelet regimens.

Background Because of the great controversy over the role of androgens in the pathogenesis of atherosclerosis, we investigated the relationship between serum sex hormone levels and angiographically confirmed coronary artery disease in men. Material and methods We investigated 86 men aged 40–60 years, 56 with coronary artery disease and 30 healthy men, matched by age, as a control group. Body mass index and waist to hip ratio were calculated and total body fat mass and percentage of abdominal deposit were investigated by dual-energy X-ray absorptiometry (Dpx ( + ) Lunar, USA). The serum levels of sex hormones and insulin were measured using commercial radioimmunoassay and IRMA (by SHBG) kits (DPC, USA). The serum levels of lipids and glucose were assessed by means of enzymatic methods. Results Men with coronary artery disease had lower total testosterone levels (17.01 ± 6.42 vs. 19.37 ± 6.58 nmol/l; p < 0.05), testosterone/estradiol ratio (228.5 ± 88.5 vs. 289.8 ± 120.1; p < 0.05) and free androgen index (FAI) (59.49 ± 14.79 vs. 83.03 ± 25.81; p < 0.0001), and higher levels of estrone (49.5 ± 27.7 vs. 36.6 ± 12.7 pg/ml) than men in the control group. Moreover, men with coronary artery disease were more insulin-resistant than controls and had an atherogenic lipid profile. There was an inverse correlation (p < 0.05) between testosterone level and serum level of glucose (r = −0.29), triglycerides (r = −0.37), body mass index (r = −0.55), waist (r = −0.43), total body fat mass (r = −0.3) and fasting insulin resistance index. A significant positive association (p < 0.05) was found between testosterone and the quantitative insulin sensitivity check index and high density lipoprotein cholesterol level in serum (r = 0.26). Conclusions Low levels of total testosterone, testosterone/estradiol ratio and free androgen index and higher levels of estrone in men with coronary artery disease appear together with many features of metabolic syndrome and may be involved in the pathogenesis of coronary atherosclerosis.

In today’s research environment characterized by exponential data growth and increasing complexity, the selection of appropriate statistical tests, tailored to research objectives and data distributions, is paramount for rigorous analysis and accurate interpretation. This article explores the growing prominence of bootstrapping, an advanced statistical technique for multiple comparisons analysis, offering flexibility and customization by estimating sample distributions without assuming population distributions, thus serving as a valuable alternative to traditional methods in various data scenarios. Computer simulations were conducted using data from cardiovascular disease patients. Two approaches, spontaneous partly controlled simulation and fully constrained simulation using self-written R scripts, were utilized to generate datasets with specified distributions and analyze the data using tests for comparing more than two groups. The utilization of the bootstrap method greatly improves statistical analysis, especially in overcoming the constraints of conventional parametric tests. Our research showcased its effectiveness in comparing multiple scenarios, yielding strong findings across diverse distributions, even with minor inflation in p values. Serving as a valuable substitute for parametric approaches, bootstrap promotes careful consideration when rejecting hypotheses, thus fostering a deeper understanding of statistical nuances and bolstering analytical rigor.