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. 2020 May 7;20(1):129.
doi: 10.1186/s12890-020-1170-6.

CT differential diagnosis of COVID-19 and non-COVID-19 in symptomatic suspects: a practical scoring method

Affiliations

CT differential diagnosis of COVID-19 and non-COVID-19 in symptomatic suspects: a practical scoring method

Lin Luo et al. BMC Pulm Med. .

Abstract

Background: Although typical and atypical CT image findings of COVID-19 are reported in current studies, the CT image features of COVID-19 overlap with those of viral pneumonia and other respiratory diseases. Hence, it is difficult to make an exclusive diagnosis.

Methods: Thirty confirmed cases of COVID-19 and forty-three cases of other aetiology or clinically confirmed non-COVID-19 in a general hospital were included. The clinical data including age, sex, exposure history, laboratory parameters and aetiological diagnosis of all patients were collected. Seven positive signs (posterior part/lower lobe predilection, bilateral involvement, rounded GGO, subpleural bandlike GGO, crazy-paving pattern, peripheral distribution, and GGO +/- consolidation) from significant COVID-19 CT image features and four negative signs (only one lobe involvement, only central distribution, tree-in-bud sign, and bronchial wall thickening) from other non-COVID-19 pneumonia were used. The scoring analysis of CT features was compared between the two groups (COVID-19 and non-COVID-19).

Results: Older age, symptoms of diarrhoea, exposure history related to Wuhan, and a lower white blood cell and lymphocyte count were significantly suggestive of COVID-19 rather than non-COVID-19 (p < 0.05). The receiver operating characteristic (ROC) curve of the combined CT image features analysis revealed that the area under the curve (AUC) of the scoring system was 0.854. These cut-off values yielded a sensitivity of 56.67% and a specificity of 95.35% for a score > 4, a sensitivity of 100% and a specificity of 23.26% for a score > 0, and a sensitivity of 86.67% and a specificity of 67.44% for a score > 2.

Conclusions: With a simple and practical scoring system based on CT imaging features, we can make a hierarchical diagnosis of COVID-19 and non-COVID-19 with different management suggestions.

Keywords: Coronavirus infections; Lung diseases; Pneumonia; Tomography, x-ray computed.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
a-d are the images of COVID-19. a Pure GGO and Rounded GGO (circle). b Mix GGO and consolidation. c Crazy-paving pattern. d Subpleural bandlike areas of GGO. e-f are the images of non-COVID-19. e Central (peribronchovascular) distribution (circle). f Tree-in-bud sign (circle)
Fig. 2
Fig. 2
ROC curve for COVID-19 prediction

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