Prevalence of COVID-19 Diagnostic Output with Chest Computed Tomography: A Systematic Review and Meta-Analysis

Background: The pooled prevalence of chest computed tomography (CT) abnormalities and other detailed analysis related to patients’ biodata like gender and different age groups have not been previously described for patients with coronavirus disease 2019 (COVID-19), thus necessitating this study. Objectives: To perform a meta-analysis to evaluate the diagnostic performance of chest CT, common CT morphological abnormalities, disease prevalence, biodata information, and gender prevalence of patients. Methods: Studies were identified by searching PubMed and Science Direct libraries from 1 January 2020 to 30 April 2020. Pooled CT positive rate of COVID-19 and RT-PCR, CT-imaging features, history of exposure, and biodata information were estimated using the quality effect (QE) model. Results: Out of 36 studies included, the sensitivity was 89% (95% CI: 80–96%) and 98% (95% CI: 90–100%) for chest CT and reverse transcription-polymerase chain reaction (RT-PCR), respectively. The pooled prevalence across lesion distribution were 72% (95% CI: 62–80%), 92% (95% CI: 84–97%) for lung lobe, 88% (95% CI: 81–93%) for patients with history of exposure, and 91% (95% CI: 85–96%) for patients with all categories of symptoms. Seventy-six percent (95% CI: 67–83%) had age distribution across four age groups, while the pooled prevalence was higher in the male with 54% (95% CI: 50–57%) and 46% (95% CI: 43–50%) in the female. Conclusions: The sensitivity of RT-PCR was higher than chest CT, and disease prevalence appears relatively higher in the elderly and males than children and females, respectively..

Medienart:

E-Artikel

Erscheinungsjahr:

2020

Erschienen:

2020

Enthalten in:

Zur Gesamtaufnahme - volume:10

Enthalten in:

Diagnostics - 10(2020), 12, p 1023

Sprache:

Englisch

Beteiligte Personen:

Temitope Emmanuel Komolafe [VerfasserIn]
John Agbo [VerfasserIn]
Ebenezer Obaloluwa Olaniyi [VerfasserIn]
Kayode Komolafe [VerfasserIn]
Xiaodong Yang [VerfasserIn]

Links:

doi.org [kostenfrei]
doaj.org [kostenfrei]
www.mdpi.com [kostenfrei]
Journal toc [kostenfrei]

Themen:

Age distribution
COVID-19
Computed tomography
Medicine (General)
Meta-analysis
Prevalence

doi:

10.3390/diagnostics10121023

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

DOAJ078725771