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Published on: December 19, 2020
Diagnostic Yield of Computed Tomography for the Identification of Coronavirus Disease 2019 Using Repeated Reverse
Davide Bellini1, Nicola Panvini1, Iacopo Carbone1
1From the Department of Radiological Sciences, Oncology and Pathology, "Sapienza" University of Rome, ICOT Hospital, Latina, Italy.
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.
