Diagnostic Yield of Computed Tomography for the Identification of Coronavirus Disease 2019 Using Repeated Reverse Transcriptase Polymerase Chain Reaction Testing or Confirmed True-Negative State as Reference Standard: Systematic Review and Meta-Analysis. Issue 6 (November 2020)

• Record Type: Journal Article
• Authors: Bellini, Davide; Panvini, Nicola; Carbone, Iacopo; Rengo, Marco; Wang, Carolyn L.; Mileto, Achille
• Is Part Of: Journal of computer assisted tomography. Volume 44:Issue 6(2020)
• Publication Date: 2020-11
• Subjects: COVID-19 -- severe acute respiratory syndrome coronavirus 2 -- tomography, x-ray computed -- diagnostic test -- sensitivity and specificity; Tomography -- Periodicals; Tomography -- Periodicals; Tomography; Periodicals; 616.0757
• DOI: 10.1097/RCT.0000000000001105
• Languages: English
• ISSNs: 0363-8715

Abstract

Abstract : Objective: The aim of this study was to perform a meta-analysis assessing the diagnostic yield of computed tomography (CT) for the identification of coronavirus disease 2019 (COVID-19) using repeated reverse transcriptase polymerase chain reaction testing or confirmed true-negative state as reference standard. Methods: In May 2020, we interrogated the MEDLINE, Embase, and CENTRAL databases. Pooled sensitivity, specificity, and diagnostic odds ratios of CT for COVID-19 identification were computed. Cumulative positive predictive value (PPV) and negative predictive value, stratified by disease prevalence, were calculated. Results: Ten articles were included (1332 patients). Pooled sensitivity, specificity, and summary diagnostic odds ratio of CT were 82% [95% confidence interval (CI), 79%–84%], 68% (95% CI, 65%–71%), and 18 (95% CI, 9.8–32.8). The PPV and negative predictive value were 54% (95% CI, 30%–77%) and 94% (95% CI, 88%–99%) at a COVID-19 prevalence lower than 40%, and 80% (95% CI, 62%–91%) and 77% (95% CI, 68%–85%) at a prevalence higher than 40%. Conclusion: CT yields higher specificity and PPV, albeit lower sensitivity, than previously reported for the identification of COVID-19.