NON-SPECIFIC ADAPTIVE REACTIONS IN PATIENTS WITH ACUTE CORONARY SYNDROME WITH ST-SEGMENT ELEVATION (STEMI) AT DIFFERENT BODY WEIGHTS

Abstract

three research groups (79 patients) were analyzed: Group I - 28 patients with STEMI and normal body weight, Group II - 24 patients with STEMI and excess body weight, and Group III - 27 patients with STEMI and obesity of the I-III degrees. The diagnosis (acute coronary syndrome) of ACS was made based on a complex clinical, laboratory and instrumental examination. Blood was taken for the study when patients were admitted to the department. The total number of leukocytes and the leukocyte blood formula were determined by standardized methods; the type of non-specific adaptation reaction - according to the method of L.H. Harkavi; the ratio of the absolute content of neutrophils to the absolute content of lymphocytes (neutrophil to lymphocyte ratio, NLR), and the ratio of the absolute content of neutrophils to the absolute content of platelets (neutrophil to platelet ratio, NPR) was determined. The course of ACS occurs against the background of several non-specific adaptation reactions, where the stress reaction was dominant (42.8% - group I, 50% - group II, and 51.9% - group III), indicating the disease's severity. The highest level of NLR (p<0.05) was found in group III, relative to the NLR indicator in group I and group II, and the highest level of NPR was found in group III precisely in case of a stress reaction, which indicates an unfavourable prognosis for patients of this group. Determining the type of nonspecific adaptation reaction can serve as an additional indicator of the severity of the patient and allows us to assess the effectiveness of therapy in patients with STEMI. The indicators of NLR and NPR were useful and powerful indicators of adverse consequences during the hospitalization of patients with ACS. The type of adaptive response and the indicators of NLR and NPR are determined based on clinical blood analysis indicators, and they are economical biomarkers for predicting the severity of inflammation.