ISSN: 1899-0967
Polish Journal of Radiology
Established by prof. Zygmunt Grudziński in 1926 Sun
Current issue Archive Manuscripts accepted About the journal Editorial board Abstracting and indexing Contact Instructions for authors Ethical standards and procedures
Editorial System
Submit your Manuscript
SCImago Journal & Country Rank
1/2022
vol. 87
 
Share:
Share:
Chest radiology
abstract:
Review article

Computed tomography scan in COVID-19: a systematic review and meta-analysis

Pouya Mahdavi Sharif
1, 2
,
Mehran Nematizadeh
1, 2
,
Mahdia Saghazadeh
1
,
Amene Saghazadeh
1, 3
,
Nima Rezaei
1, 3, 4, 5

1.
Systematic Review and Meta-analysis Expert Group (SRMEG), Universal Scientific Education and Research Network (USERN), Tehran, Iran
2.
School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
3.
Research Center for Immunodeficiencies, Children’s Medical Center, Tehran University of Medical Sciences, Tehran, Iran
4.
Department of Immunology, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
5.
Network of Immunity in Infection, Malignancy and Autoimmunity (NIIMA), Universal Scientific Education and Research Network (USERN), Tehran, Iran
Pol J Radiol 2022; 87: e1-e23
Online publish date: 2022/01/05
View full text Get citation
 
PlumX metrics:
Introduction
Computed tomography (CT) scan is a commonly used tool for the diagnosis of the novel coronavirus disease 2019 (COVID-19), similarly to reverse transcription-polymerase chain reaction (RT-PCR). Because of the limitations of RT-PCR, there is growing interest in the usability of the CT scan. The present systematic review and meta-analysis aims to summarize the available data on the CT scan features of COVID-19.

Material and methods
We conducted a systematic search in electronic databases to find eligible studies published between 1 December 2019 and 4 April 2020, which investigated the computed tomographic features of patients with COVID-19. All preprint and peer-reviewed articles were included. No language limitation was applied. For proportional data, pooled prevalence was calculated using a Freeman-Tukey double arcsine transformation, with a 95% confidence interval (CI).

Results
Eighty-six studies were eligible to be included in the meta-analysis. For 7956 patients, the most common CT findings were bilateral pattern of involvement (78%; 95% CI: 0.73-0.82; p < 0.001), involvement of more than 1 lobe (75%; 95% CI: 0.68-0.82; p < 0.001), ground-glass opacities (GGO) (73%; 95% CI: 0.67-0.78; p < 0.001), and periphe­ral distribution of signs (69%; 95% CI: 0.61-0.76; p < 0.001). Only 5% of patients had a normal CT scan (95% CI: 0.03-0.07; p < 0.001). The proportion of paediatric patients (age < 18 years) with unremarkable CT findings was higher (40%; 95% CI: 0.27-0.55; p < 0.001). Subgroup analysis showed that patients with the severe or critical type of COVID-19 were more likely to have pleural effusion (RR 7.77; 95% CI: 3.97-15.18; p < 0.001) and consolidation (RR 3.13; 95% CI: 1.57-6.23; p < 0.001). CT results in patients with COVID-19 were comparable with those of people having pneumonia from other causes, except for the lower incidence of consolidation (RR 0.81; 95% CI: 0.71-0.91; p < 0.001) and higher risk of showing GGO (RR 1.45; 95% CI: 1.13-1.86; p < 0.001). The mortality rate was slightly higher in patients with bilateral involvement (RR 3.19; 95% CI: 1.07-9.49; p = 0.04).

Conclusions
Our study results show that COVID-19 shares some features with other viral types of pneumonia, despite some differences. They commonly present as GGO along with vascular thickening, air bronchogram and consolidations. Normal CT images, lymphadenopathies, and pleural effusions are not common. Consolidations and pleural effusions correlate with more severe disease. CT features are different between COVID-19 and non-COVID-19 pneumonia. Also, they differ by age, disease severity, and outcomes within COVID-19 patients.

keywords:

COVID-19, SARS-CoV-2, computed tomography, CT scan, imaging, systematic review, meta-analysis, paediatric, ground-glass opacities




Quick links
© 2024 Termedia Sp. z o.o.
Developed by Bentus.