PropertyValue
?:abstract
  • OBJECTIVES: To evaluate the clinical pictures, laboratory tests and imaging of patients with lung involvement, either from severe COVID-19 or macrophage activation syndrome (MAS), in order to assess how similar these two diseases are. METHODS: The present work has been designed as a cross-sectional single-centre study to compare characteristics of patients with lung involvement either from MAS or severe COVID-19. Chest CT scans were assessed by using an artificial intelligence (AI)-based software. RESULTS: Ten patients with MAS and 47 patients with severe COVID-19 with lung involvement were assessed. Although all patients showed fever and dyspnoea, patients with MAS were characterised by thrombocytopaenia, whereas patients with severe COVID-19 were characterised by lymphopaenia and neutrophilia. Higher values of H-score characterised patients with MAS when compared with severe COVID-19. AI-reconstructed images of chest CT scan showed that apical, basal, peripheral and bilateral distributions of ground-glass opacities (GGOs), as well as apical consolidations, were more represented in severe COVID-19 than in MAS. C reactive protein directly correlated with GGOs extension in both diseases. Furthermore, lymphopaenia inversely correlated with GGOs extension in severe COVID-19. CONCLUSIONS: Our data could suggest laboratory and radiological differences between MAS and severe COVID-19, paving the way for further hypotheses to be investigated in future confirmatory studies.
?:creator
?:doi
  • 10.1136/annrheumdis-2020-218048
?:doi
?:journal
  • Ann_Rheum_Dis
?:license
  • no-cc
?:pdf_json_files
  • document_parses/pdf_json/1632c80505113462859504ce1efa19ca6d318985.json
?:pmc_json_files
  • document_parses/pmc_json/PMC7456556.xml.json
?:pmcid
?:pmid
?:pmid
  • 32719039.0
?:publication_isRelatedTo_Disease
?:sha_id
?:source
  • Medline; PMC
?:title
  • Lung involvement in macrophage activation syndrome and severe COVID-19: results from a cross-sectional study to assess clinical, laboratory and artificial intelligence–radiological differences
?:type
?:year
  • 2020-07-21

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