Associations between CT pulmonary opacity score on admission and clinical characteristics and outcomes in patients with COVID-19
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AbstractThis study investigated associations between chest computed tomography (CT) pulmonary opacity score on admission and clinical features and outcomes in COVID-19 patients. The retrospective multi-center cohort study included 496 COVID-19 patients in Jiangsu province, China diagnosed as of March 15, 2020. Patients were divided into four groups based on the quartile of pulmonary opacity score: ≤ 5%, 6–20%, 21–40% and 41% +. CT pulmonary opacity score was independently associated with age, single onset, fever, cough, peripheral capillary oxygen saturation, lymphocyte count, platelet count, albumin level, C-reactive protein (CRP) level and fibrinogen level on admission. Patients with score ≥ 41% had a dramatic increased risk of severe or critical illness [odds ratio (OR), 15.58, 95% confidence interval (CI) 3.82–63.53), intensive care unit (ICU)] admission (OR, 6.26, 95% CI 2.15–18.23), respiratory failure (OR, 19.49, 95% CI 4.55–83.40), and a prolonged hospital stay (coefficient, 2.59, 95% CI 0.46–4.72) compared to those with score ≤ 5%. CT pulmonary opacity score on admission, especially when ≥ 41%, was closely related to some clinical characteristics and was an independent predictor of disease severity, ICU admission, respiratory failure and long hospital stay in patients with COVID-19.
CitationLuo, H., Wang, Y., Liu, S., Chen, R., Chen, T., Yang, Y., Wang, D. and Ju, S. (2021) Associations between CT pulmonary opacity score on admission and clinical characteristics and outcomes in patients with COVID-19'. Internal and emergency medicine, Vol 2021.
JournalInternal and Emergency Medicine
PubMed ID34191219 (pubmed)
DescriptionThis is an accepted manuscript of an article published by Springer in Internal and Emergency Medicine on 30/06/2021, available online: https://doi.org/10.1007/s11739-021-02795-9 The accepted version of the publication may differ from the final published version.
SponsorsThis work was supported, in part, by the research Grant 2020YFC0843700 67 from Ministry of Science and Technology of the People’s Republic of China.
Except where otherwise noted, this item's license is described as https://creativecommons.org/licenses/by-nc-nd/4.0/
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