Researchers at the Instituto de Química de São Carlos (IQSC), at the University of São Paulo, have identified a method with the potential to predict the severity of Covid-19 infection in patients, based on the analysis of blood plasma. The system can serve as a screening tool in the care of those infected and be used in order to prevent the evolution of the disease. The study was published in the scientific journal Journal of Proteome Research.
According to the research, patients infected by the disease had variations in the concentration of six substances found in the blood, called metabolites, which are glycerol, acetate, 3-aminoisobutyrate, formate, glucuronate and lactate. The analyzes revealed that the greater the imbalance in the amount of these substances at the beginning of the infection, the more serious the health conditions that the patients developed.
Plasma
Blood plasma samples from 110 patients with flu symptoms who passed through the Hospital of the Federal University of São Paulo (Unifesp) were analyzed in 2020, 57 of whom were not infected with covid-19 and the other 53 were recent positive cases of the disease. illness.
The researchers observed that, of those infected, ten patients had complications and were admitted to the Intensive Care Unit (ICU), with two deaths recorded. This group with a more severe condition presented, at the beginning of the covid-19 infection, more accentuated variations in the concentration of the aforementioned metabolites.
The results of the study may contribute, as pointed out by the IQSC, to the development of a new clinical protocol that would help doctors and hospitals to identify, in the first days of symptoms, patients who may develop the severe form of the disease, allowing them to intervene to avoid the evolution of the disease.
Also according to the IQSC, to validate the technique, the researchers plan to expand the number of blood plasma samples evaluated and include new groups, such as vaccinated people who contracted Covid-19, in the next steps of the study. In addition, they intend to include gender and age information in the statistics.
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