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

Abstract

Purpose: Computed tomography (CT) scan is a commonly used tool for the diagnosis of the novel coronavirus disease 2019 , 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 periphe ral 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;; 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.

The value of lung ultrasound in COVID-19 pneumonia, verified by high resolution computed tomography assessed by artificial intelligence

“…The most common HRCT findings in COVID-19 pneumonia include ground glass opacities, vascular redistribution, followed by air-bronchogram, consolidations and crazy paving pattern [4]. Typically both lungs are involved, with peripheral distribution of lesions, involvement of more than one lobe and predilection to lower lobes.…”

Chest CT Scan Features of COVID-19 in a Hospitalized High-Altitude Population

“…Sharif et al published a meta-analysis in 2022 [22]. The researchers reviewed 86 reports of chest CT scan evaluations in COVID-19, totaling 7956 patients.…”

“…Sharif's meta-analysis [22] found that the left lower lobe was involved in 67% of cases and the right in 66%, while the right middle lobe was the least commonly involved. Most cases in our population were in the peak phase (48.7%), followed by the progressive phase in 30.59%.…”

Factors Associated with COVID-19 Death in a High-Altitude Peruvian Setting during the First 14 Months of the Pandemic: A Retrospective Multicenter Cohort Study in Hospitalized Patients

“…RT-PCR and antigen tests have comparable diagnostic utility, whereas the diagnostic use of serology has been widely discussed in acute disease [ 62 , 63 , 64 ]. Furthermore, the use of CT scans in the diagnosis of COVID-19 is not perfect, and the identification of infiltrate could vary between observers [ 65 , 66 , 67 ]. Despite the use of a composite definition for COVID-19 death, the use of this definition did not overcome the bias inherent to each test used to construct the definition [ 68 , 69 ].…”