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Distinguishing COVID-19 from influenza pneumonia in the early stage through CT imaging and clinical features
Zhiqi Yang; Daiying Lin; Xiaofeng Chen; Jinming Qiu; Shengkai Li; Ruibin Huang; Hongfu Sun; Yuting Liao; Jianning Xiao; Yanyan Tang; Guorui Liu; Renhua Wu; Xiangguang Chen; Zhuozhi Dai.
Afiliación
  • Zhiqi Yang; Department of Radiology, Meizhou People`s Hospital, Guangdong, 514031, P. R. China.
  • Daiying Lin; Department of Radiology, Shantou Central Hospital, Shantou, Guangdong, 515041, P. R. China.
  • Xiaofeng Chen; Department of Radiology, Meizhou People`s Hospital, Guangdong, 514031, P. R. China
  • Jinming Qiu; Department of Radiology, Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, 515000, P. R. China
  • Shengkai Li; Department of Radiology, Huizhou Municipal Central Hospital, Huizhou, Guangdong 516001, China.
  • Ruibin Huang; Department of Radiology, First Affiliated Hospital, Shantou University Medical College, Shantou, Guangdong, 515041, P. R. China.
  • Hongfu Sun; School of Information Technology and Electrical Engineering, University of Queensland, Queensland, 4072, Australia.
  • Yuting Liao; GE Healthcare, Guangzhou 510623, China.
  • Jianning Xiao; Department of Radiology, Shantou Central Hospital, Shantou, Guangdong, 515041, P. R. China.
  • Yanyan Tang; Department of Radiology, Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, 515000, P. R. China
  • Guorui Liu; Department of Radiology, Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, 515000, P. R. China
  • Renhua Wu; Department of Radiology, Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, 515000, P. R. China
  • Xiangguang Chen; Department of Radiology, Meizhou People`s Hospital, Guangdong, 514031, P. R. China.
  • Zhuozhi Dai; Second Affiliated Hospital of Shantou University Medical College
Preprint en En | PREPRINT-MEDRXIV | ID: ppmedrxiv-20061242
ABSTRACT
PurposeTo identify differences in CT imaging and clinical features between COVID-19 and influenza pneumonia in the early stage, and to identify the most valuable features in the differential diagnosis. Materials and MethodA consecutive cohort of 73 COVID-19 and 48 influenza pneumonia patients were retrospectively recruited from five independent institutions. The courses of both diseases were confirmed to be in the early stages (2.66 {+/-} 2.62 days for COVID-19 and 2.19 {+/-} 2.10 days for influenza pneumonia after onset). The chi-square test, students t-test, and Kruskal-Wallis H-test were performed to compare CT imaging and clinical features between the two groups. Spearman or Kendall correlation tests between feature metrics and diagnosis outcomes were also assessed. The diagnostic performance of each feature in differentiating COVID-19 from influenza pneumonia was evaluated with univariate analysis. The corresponding area under the curve (AUC), accuracy, specificity, sensitivity and threshold were reported. ResultsThe ground-glass opacification (GGO) was the most common imaging feature in COVID-19, including pure-GGO (75.3%) and mixed-GGO (78.1%), mainly in peripheral distribution. For clinical features, most COVID-19 patients presented normal white blood cell (WBC) count (89.04%) and neutrophil count (84.93%). Twenty imaging features and 6 clinical features were identified to be significantly different between the two diseases. The diagnosis outcomes correlated significantly with the WBC count (r=-0.526, P<0.001) and neutrophil count (r=-0.500, P<0.001). Four CT imaging features had absolute correlations coefficients higher than 0.300 (P<0.001), including crazy-paving pattern, mixed-GGO in peripheral area, pleural effusions, and consolidation. ConclusionsAmong a total of 1537 lesions and 62 imaging and clinical features, 26 features were demonstrated to be significantly different between COVID-19 and influenza pneumonia. The crazy-paving pattern was recognized as the most powerful imaging feature for the differential diagnosis in the early stage, while WBC count yielded the highest diagnostic efficacy in clinical manifestations.
Licencia
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Texto completo: 1 Colección: 09-preprints Base de datos: PREPRINT-MEDRXIV Tipo de estudio: Cohort_studies / Diagnostic_studies / Experimental_studies / Observational_studies / Prognostic_studies / Rct Idioma: En Año: 2020 Tipo del documento: Preprint
Texto completo: 1 Colección: 09-preprints Base de datos: PREPRINT-MEDRXIV Tipo de estudio: Cohort_studies / Diagnostic_studies / Experimental_studies / Observational_studies / Prognostic_studies / Rct Idioma: En Año: 2020 Tipo del documento: Preprint