Blood Group as a Predictor of Glycemia and Lactatemia in Critical Condition Patients

Abstract

Hyperlactatemia is a dangerous metabolic shift, manifested in an increase in the blood lactate content above 2.2 mmol / l. Changes in the content of lactate affect the function of vital organs and systems, disrupting the course of biochemical processes. This condition accompanies a large number of clinical situations, also it is a major factor, worsening the clinical outcome and the patient’s condition. The study of the characteristics of its occurrence and metabolic relationships helps to fulfill the diagnostic criteria for assessing the likelihood of an adverse outcome. The purpose of this study is to assess the variability of the content of lactate and glucose, as well as the glucose/lactate ratio, depending on the group of blood in the ABO system and the nosology of patients. 250 patients with various diseases whose condition required intensive care were examined, the middle age was 61.08 ± 13.6 years, and 446 practically healthy individuals who did not have acute somatic and infectious diseases, the middle age was 26.83 ± 1.46 years . We investigated the content of lactate and glucose, the glucose/lactate ratio, determined the belonging of the blood to ABO system. Statistical processing of the results was performed in the IBM SPSS Statistica 23.0. The data obtained indicate that patients with B (III) blood group have the highest lactate content in venous blood compared to the general population, and patients with AB (IV) blood group have the highest blood glucose level. In the group of patients with the highest median lactate content, the lowest glucose content was observed. The data presented demonstrate the importance of measuring and monitoring glucose, lactate, and their ratio in the management of patients in a life-threatening condition. Evaluation of metabolic variability depending on the different blood grouping of the ABO system in critical conditions involving hyperlactataemia can serve as an important tool in modeling a personalized approach to the patient.