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.