Lung Ultrasound and High-Resolution Computed Tomography in Suspected COVID-19 Patients Admitted to the Emergency Department: A Comparison
- PMID: 38603205
- PMCID: PMC9892814
- DOI: 10.1177/87564793221147496
Lung Ultrasound and High-Resolution Computed Tomography in Suspected COVID-19 Patients Admitted to the Emergency Department: A Comparison
Abstract
Objective: To analyze the diagnostic accuracy of lung ultrasonography (LUS) and high-resolution computed tomography (HRCT), to detect COVID-19.
Materials and methods: This study recruited all patients admitted to the emergency medicine unit, due to a suspected COVID-19 infection, during the first wave of the COVID-19 pandemic. These patients also who underwent a standardized LUS examination and a chest HRCT. The signs detected by both LUS and HRCT were reported, as well as the sensitivity, specificity, positive predictive value, and negative predictive value for LUS and HRCT.
Results: This cohort included 159 patients, 101 (63%) were diagnosed with COVID-19. COVID-19 patients showed more often confluent subpleural consolidations and parenchymal consolidations in lower lung regions of LUS. They also had "ground glass" opacities and "crazy paving" on HRCT, while pleural effusion and pulmonary consolidations were more common in non-COVID-19 patients. LUS had a sensitivity of 0.97 (95% CI 0.92-0.99) and a specificity of 0.24 (95% CI 0.07-0.5) for COVID-19 lung infections. HRCT abnormalities resulted in a 0.98 sensitivity (95% CI 0.92-0.99) and 0.1 specificity (95% CI 0.04-0.23) for COVID-19 lung infections.
Conclusion: In this cohort, LUS proved to be a noninvasive, diagnostic tool with high sensitivity for lung abnormalities that were likewise detected by HRCT. Furthermore, LUS, despite its lower specificity, has a high sensitivity for COVID-19, which could prove to be as effective as HRCT in excluding a COVID-19 lung infection.
Keywords: COVID-19; lung diseases; lung infiltrates; lung ultrasonography.
© The Author(s) 2023.
Conflict of interest statement
The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
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