| Autor: |
Artem V. Obkhodskiy, Victor I. Sachkov, Evgeniy L. Choynzonov, Elena V. Obkhodskaya, E.O. Rodionov, O.M. Vinogradova, Anna S. Sachkova, Denis E. Kulbakin, Ekaterina N. Menkova, V. I. Chernov, Aleksandr S. Popov, I. Amelichkin |
| Rok vydání: |
2021 |
| Předmět: |
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| Zdroj: |
SSRN Electronic Journal. |
| ISSN: |
1556-5068 |
| Popis: |
Background: One of the most relevant issue today is the diagnosis of COVID-19 at an early stage. A non-invasive approach to study exhaled air compositions can be used in solving the problem. Methods: The patients with COVID-19, with pneumonia unrelated to COVID-19, and healthy persons took part in the experiments. Samples of the exhaled air were analyzed by the gas analysis system - artificial neural network with a set of semiconductor gas sensors that characterizes the qualitative and quantitative composition of chemical compounds in the exhaled air. Findings: Analysis of the gas composition of the exhaled air of the patients with COVID-19 showed almost complete absence of molecular complex metabolic products (esters, alcohols, etc.). It is a characteristic sign of impairment of gas exchange at the level of alveolus-capillary and can be a diagnostic marker of the patients with COVID-19.The results of differential diagnosis in the classification of the healthy persons and the patients with disease at the level of sensitivity were 97.36 % and specificity - 98.63 %. Moreover, this system is able to differentiate cases of COVID-19 among the patients with inflammatory lung diseases not related to COVID-19 (sensitivity - 97.5 % and specificity - 92.11 %). Interpretation: Since the biochemical processes that occur with COVID-19 and community-acquired pneumonia are different, the gas sensors can provide detection of the characteristic features of the gas composition of exhaled air that are characteristic for an individual disease. The method is an effective tool in express diagnostics of COVID-19 and pneumonia, that may have a positive impact on clinical practice. Funding: None. Declaration of Interests: No potential conflicts of interest were disclosed. Ethics Approval Statement: The study was approved by the bioethical Committee of the Cancer Research Institute, Tomsk National Research Medical Center of the Russian Academy of Sciences (order on creation No. 57-r dated 23.12.2010). |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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