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10.1097/RLI.0000000000000689

http://scihub22266oqcxt.onion/10.1097/RLI.0000000000000689
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32304402!7173027!32304402
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suck abstract from ncbi


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pmid32304402      Invest+Radiol 2020 ; 55 (7): 412-421
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  • The Performance of Chest CT in Evaluating the Clinical Severity of COVID-19 Pneumonia: Identifying Critical Cases Based on CT Characteristics #MMPMID32304402
  • Lyu P; Liu X; Zhang R; Shi L; Gao J
  • Invest Radiol 2020[Jul]; 55 (7): 412-421 PMID32304402show ga
  • OBJECTIVES: The aim of this study was to assess the clinical severity of COVID-19 pneumonia using qualitative and/or quantitative chest computed tomography (CT) indicators and identify the CT characteristics of critical cases. MATERIALS AND METHODS: Fifty-one patients with COVID-19 pneumonia including ordinary cases (group A, n = 12), severe cases (group B, n = 15), and critical cases (group C, n = 24) were retrospectively enrolled. The qualitative and quantitative indicators from chest CT were recorded and compared using Fisher exact test, one-way analysis of variance, Kruskal-Wallis H test, and receiver operating characteristic analysis. RESULTS: Depending on the severity of the disease, the number of involved lung segments and lobes, the frequencies of consolidation, crazy-paving pattern, and air bronchogram increased in more severe cases. Qualitative indicators including total severity score for the whole lung and total score for crazy-paving and consolidation could distinguish groups B and C from A (69% sensitivity, 83% specificity, and 73% accuracy) but were similar between group B and group C. Combined qualitative and quantitative indicators could distinguish these 3 groups with high sensitivity (B + C vs A, 90%; C vs B, 92%), specificity (100%, 87%), and accuracy (92%, 90%). Critical cases had higher total severity score (>10) and higher total score for crazy-paving and consolidation (>4) than ordinary cases, and had higher mean lung density (>-779 HU) and full width at half maximum (>128 HU) but lower relative volume of normal lung density (<==50%) than ordinary/severe cases. In our critical cases, 8 patients with relative volume of normal lung density smaller than 40% received mechanical ventilation for supportive treatment, and 2 of them had died. CONCLUSIONS: A rapid, accurate severity assessment of COVID-19 pneumonia based on chest CT would be feasible and could provide help for making management decisions, especially for the critical cases.
  • |Adult[MESH]
  • |Aged[MESH]
  • |Aged, 80 and over[MESH]
  • |Betacoronavirus/*pathogenicity[MESH]
  • |COVID-19[MESH]
  • |Coronavirus Infections/*diagnostic imaging/*pathology[MESH]
  • |Female[MESH]
  • |Humans[MESH]
  • |Lung/*diagnostic imaging[MESH]
  • |Male[MESH]
  • |Middle Aged[MESH]
  • |Pandemics[MESH]
  • |Pneumonia, Viral/*diagnostic imaging/*pathology[MESH]
  • |ROC Curve[MESH]
  • |Radiography, Thoracic/methods[MESH]
  • |Reproducibility of Results[MESH]
  • |Retrospective Studies[MESH]
  • |SARS-CoV-2[MESH]
  • |Severity of Illness Index[MESH]


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