Acute viral respiratory infections add to the progression risk of the already existing pathologies, including those of cardiovascular origin. Life-threatening complications emerging against SARS-CoV-2 (severe acute respiratory syndrome), which causes COVID-19 (Coronavirus disease 2019), explain the need to study the cardiovascular effects of COVID-19 in order to offer rational medical care to patients belonging to various age categories. This article presents a comprehensive assessment of changes affecting the main hemostasis parameters in patients with acute cerebral circulatory disorders against the SARS-CoV-2 virus infection. There is special attention paid to the pathophysiological features occurring against the infectious process involving the hemostasis system. Our data shows that the differences in the main hemostatic parameters in patients with acute cerebral circulatory disorders occurring against the SARS-CoV-2 virus infection are due to the degree of the body responsiveness and the severity of the comorbid pathology. Reducing the risk of adverse conditions developing in this category of patients is possible in case of responsible monitoring focusing on the main indicators of the cardiovascular system status, as well as provided there are advanced approaches introduced in order to prevent and treat thrombotic/thromboembolic complications.

presents findings of the research investigating the effect of various glucose concentrations on the morphometric parameters of red blood cells. The principal component method was employed in order to determine the most significant indicators in the experiment. The experiment was aimed to investigate the effect of hyperglycemia on the shape, size and functional parameters of erythrocytes depending on the glucose concentration and exposure time. It was established that characteristic changes in the shape and size of erythrocytes induced by hyperglycemia are correlative with concentration of glucose and exposure time.K E Y w O R D S -glucose concentration, red blood cells, morphometric parameters, principal component analysis.