In:
BMC Medicine, Springer Science and Business Media LLC, Vol. 19, No. 1 ( 2021-12)
Kurzfassung:
Knowledge about the 1-year outcome of COVID-19 is limited. The aim of this study was to follow-up and evaluate lung abnormalities on serial computed tomography (CT) scans in patients with COVID-19 after hospital discharge. Methods A prospective cohort study of patients with COVID-19 from the First Affiliated Hospital, Zhejiang University School of Medicine was conducted, with assessments of chest CT during hospitalization and at 2 weeks, 1 month, 3 months, 6 months, and 1 year after hospital discharge. Risk factors of residual CT opacities and the influence of residual CT abnormalities on pulmonary functions at 1 year were also evaluated. Results A total of 41 patients were followed in this study. Gradual recovery after hospital discharge was confirmed by the serial CT scores. Around 47% of the patients showed residual aberration on pulmonary CT with a median CT score of 0 (interquartile range (IQR) of 0–2) at 1 year after discharge, with ground-glass opacity (GGO) with reticular pattern as the major radiologic pattern. Patients with residual radiological abnormalities were older ( p = 0.01), with higher rate in current smokers ( p = 0.04), higher rate in hypertensives ( p = 0.05), lower SaO 2 ( p = 0.004), and higher prevalence of secondary bacterial infections during acute phase ( p = 0.02). Multiple logistic regression analyses indicated that age was a risk factor associated with residual radiological abnormalities (OR 1.08, 95% CI 1.01–1.15, p = 0.02). Pulmonary functions of total lung capacity ( p = 0.008) and residual volume ( p 〈 0.001) were reduced in patients with residual CT abnormalities and were negatively correlated with CT scores. Conclusion During 1-year follow-up after discharge, COVID-19 survivors showed continuous improvement on chest CT. However, residual lesions could still be observed and correlated with lung volume parameters. The risk of developing residual CT opacities increases with age.
Materialart:
Online-Ressource
ISSN:
1741-7015
DOI:
10.1186/s12916-021-02056-8
Sprache:
Englisch
Verlag:
Springer Science and Business Media LLC
Publikationsdatum:
2021
ZDB Id:
2131669-7
