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Chest CT imaging characteristics and their evolution of 48 patients with COVID-19 in Hengyang, China
American Journal of Translational Research ; 13(9):9983-9992, 2021.
Article in English | EMBASE | ID: covidwho-1456892
ABSTRACT
The novel coronavirus 2019 (2019 nCoV), appeared in Wuhan in December 2019, can cause a novel coronavirus pneumonia (Corona Virus Disease 2019, COVID-19). COVID-19 is highly infectious and easy to infect people. The epidemic has gradually spread to all parts of the country. In order to provide a basis for clinical diagnosis, this study retrospectively analyzed the imaging characteristics, evolution and related imaging manifestations of COVID-19 patients in different stages of the disease. The results suggest that the imaging findings of 48 COVID-19 patients from Hengyang, Hunan Province are comparable in different stages of the disease. Chest CT showed no pneumonia in one mild patient. Chest CT findings of moderate type (n=38) and severe type (n=9) had comparable characteristics. The main manifestations were ground-glass opacity (GGO) (18/38, 47.37%;1/9, 11.11%), and GGO with consolidation (16/38, 42.11%;5/9, 55.56%), which respectively presented in bilateral lungs (34/38, 89.47%;9/9, 100.00%), and multi-lobe distribution (involving 5 lobes) (17/38, 44.74%;8/9, 88.89%). After treatment, 28 patients were isolated for 14 days and returned to the hospital for re-examination;among them, the pulmonary lesion was completely absorbed in 15 moderate patients, while 13 patients mainly manifested as GGO. The CT imaging findings of patients with COVID-19 can detect the lesions early, observe the scope of the lesions, evaluate the severity of the lesions, and assist the clinician in completing rapid isolation, diagnosis and treatment. At the same time, it can help to understand the performance of COVID-19 in different stages and dynamically detect changes in the patient's condition.
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Collection: Databases of international organizations Database: EMBASE Language: English Journal: American Journal of Translational Research Year: 2021 Document Type: Article

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Collection: Databases of international organizations Database: EMBASE Language: English Journal: American Journal of Translational Research Year: 2021 Document Type: Article