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Research Article
Computed Tomography and Clinical Features Differentiating Coronavirus Disease 2019 from Seasonal Influenza Pneumonia
Bin Song
Sichuan University West China Hospital
Corresponding Author
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Objectives: To investigate computed tomography (CT) and clinical features could help differentiate coronavirus disease 2019 (COVID-19) from seasonal influenza pneumonia.
Methods: We retrospectively evaluated the clinical features and chest CT findings of Chinese patients with COVID-19 and seasonal influenza pneumonia treated during the same period.
Results: The 24 patients with COVID-19 (mean age, 41 years; 13 men) and 79 patients with seasonal influenza pneumonia (mean age, 41 years; 50 men) differed significantly in mean temperature, respiratory rate, and systolic blood pressure; in central-peripheral, superior-inferior, and anterior-posterior distribution but not lateral distribution of pulmonary lesions; and patchy ground-glass opacity (GGO), GGO nodules, vascular enlargement in GGO, air bronchogram, bronchiolectasis in GGO or consolidation, interlobular septal thickening, and crazy-paving pattern. Separate regression models were developed with clinical features, CT features (including anatomical distributions), and a combined model informed by the first two. The combined model had the best diagnostic performance for identifying COVID-19: a cut-off value of 0.38 was 74% sensitive and 100% specific and had an area under the receiver operating characteristics curve of 0.94. This model was based on sputum production, vascular enlargement in GGO, and central-peripheral distribution (random vs subpleural).
Conclusions: The combination of sputum production, vascular enlargement in GGO, and central-peripheral distribution should be extremely helpful in the differential diagnosis of COVID-19.
Keywords
Infection; Coronavirus; Influenza, Human; Pneumonia, Viral; Tomography, X-ray computed
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This is a preprint. It has not completed peer review.
Research Article
Computed Tomography and Clinical Features Differentiating Coronavirus Disease 2019 from Seasonal Influenza Pneumonia
Bin Song
Sichuan University West China Hospital
Corresponding Author
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
History
CURRENT STATUS: Posted
Version 1
Posted 26 May, 2020
No community comments so far
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Objectives: To investigate computed tomography (CT) and clinical features could help differentiate coronavirus disease 2019 (COVID-19) from seasonal influenza pneumonia.
Methods: We retrospectively evaluated the clinical features and chest CT findings of Chinese patients with COVID-19 and seasonal influenza pneumonia treated during the same period.
Results: The 24 patients with COVID-19 (mean age, 41 years; 13 men) and 79 patients with seasonal influenza pneumonia (mean age, 41 years; 50 men) differed significantly in mean temperature, respiratory rate, and systolic blood pressure; in central-peripheral, superior-inferior, and anterior-posterior distribution but not lateral distribution of pulmonary lesions; and patchy ground-glass opacity (GGO), GGO nodules, vascular enlargement in GGO, air bronchogram, bronchiolectasis in GGO or consolidation, interlobular septal thickening, and crazy-paving pattern. Separate regression models were developed with clinical features, CT features (including anatomical distributions), and a combined model informed by the first two. The combined model had the best diagnostic performance for identifying COVID-19: a cut-off value of 0.38 was 74% sensitive and 100% specific and had an area under the receiver operating characteristics curve of 0.94. This model was based on sputum production, vascular enlargement in GGO, and central-peripheral distribution (random vs subpleural).
Conclusions: The combination of sputum production, vascular enlargement in GGO, and central-peripheral distribution should be extremely helpful in the differential diagnosis of COVID-19.
Figure 1
Figure 2
Figure 3
Figure 4