Open AccessEvolution of CT patterns in novel coronavirus (2019-nCoV) pneumonia in relation to clinical and laboratory data
Author(s) -
А. А. Oganesyan,
I. V. Shrainer,
В. Н. Виноградов,
Е. С. Першина,
E. G. Koshelev,
Dmitry Shchekochikhin,
Alexandra Shilova,
M. Yu. Gilyarov,
Aleksei V. Svet
Publication year - 2021
Publication title -
lučevaâ diagnostika i terapiâ
Language(s) - English
Resource type - Journals
eISSN - 2079-5351
pISSN - 2079-5343
DOI - 10.22328/2079-5343-2021-12-2-49-58
Subject(s) - pneumonia , coronavirus , covid-19 , medicine , disease , pandemic , radiology , infectious disease (medical specialty)
. The CT patterns of coronavirus pneumonia are clear and represent certain pathomorphosis at the period of coronavirus pandemic. However, there are a lot of questions about influence of CT-patterns and their dynamic change on a disease’s severity. The aim of the study. To evaluate the dynamics of pulmonary CT changes of novel coronavirus (2019-nCoV) pneumonia in relation to clinical and laboratory data. Materials and methods. CT studies in dynamics of 108 patients with a of novel coronavirus (2019-nCoV) pneumonia were analyzed. The first CT study was performed on admission (6,7±4,1 days of the disease), the first control CT on 11,1±4,9 days of the disease, and the second CT control was performed on 16,7±5,6 days of the disease. Results. The volume of the lesion and the predominant CT symptom at admission did not affect the prognosis. However, changes in the repeated CT study had a high prognostic value. Thus, the occurrence of a pattern of organizing pneumonia during repeated study is associated with a good prognosis, while an increase in the zones of «crazy paving» and a larger volume of damage are unfavorable prognostic signs. An increase in the volume of changes in the type of ground glass and «crazy paving» correlated with increased levels of C-reactive protein, lactate dehydrogenase, and lymphopenia. Conclusion. Data from CT studies in dynamics for novel coronavirus (2019-nCoV) pneumonia have a prognostic value and, in combination with clinical and laboratory data, can influence decision-making on patient management.