Low-dose chest CT for diagnosing and assessing the extent of lung involvement of SARS-CoV-2 pneumonia using a semi quantitative score - Archive ouverte HAL Access content directly
Journal Articles PLoS ONE Year : 2020

Low-dose chest CT for diagnosing and assessing the extent of lung involvement of SARS-CoV-2 pneumonia using a semi quantitative score

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Abstract

Objectives The purpose is to assess the ability of low-dose CT (LDCT) to determine lung involvement in SARS-CoV-2 pneumonia and to describe a COVID19-LDCT severity score. Materials and methods Patients with SARS-CoV-2 infection confirmed by RT-PCR were retrospectively analysed. Clinical data, the National Early Warning Score (NEWS) and imaging features were recorded. Lung features included ground-glass opacities (GGO), areas of consolidation and crazy paving patterns. The COVID19-LDCT score was calculated by summing the score of each segment from 0 (no involvement) to 10 (severe impairment). Univariate analysis was performed to explore predictive factor of high COVID19-LDCT score. The nonparametric Mann-Whitney test was used to compare groups and a Spearman correlation used with p<0.05 for significance. Results Eighty patients with positive RT-PCR were analysed. The mean age was 55 years +/- 16, with 42 males (53%). The most frequent symptoms were fever (60/80, 75%) and cough (59/80, 74%), the mean NEWS was 1.7 +/- 2.3. All LDCT could be analysed and 23/80 (28%) were normal. The major imaging finding was GGOs in 56 cases (67%). The COVID19-LDCT score (mean value = 19 +/- 29) was correlated with NEWS (r = 0.48, p<0.0001). No symptoms were risk factor to have pulmonary involvement. Univariate analysis shown that dyspnea, high respiratory rate, hypertension and diabetes are associated to a COVID19-LDCT score superior to 50. Conclusions COVID19-LDCT score did correlate with NEWS. It was significantly different in the clinical low-risk and high-risk groups. Further work is needed to validate the COVID19-LDCT score against patient prognosis.

Dates and versions

hal-03149252 , version 1 (22-02-2021)

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Thomas Leger, Alexis Jacquier, Pierre-Antoine Barral, Maxime Castelli, Julie Finance, et al.. Low-dose chest CT for diagnosing and assessing the extent of lung involvement of SARS-CoV-2 pneumonia using a semi quantitative score. PLoS ONE, 2020, 15 (11), ⟨10.1371/journal.pone.0241407⟩. ⟨hal-03149252⟩
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