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10.5152/dir.2020.20351

http://scihub22266oqcxt.onion/10.5152/dir.2020.20351
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32558646!7360076!32558646
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suck abstract from ncbi


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pmid32558646      Diagn+Interv+Radiol 2020 ; 26 (4): 315-322
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  • COVID-19 S: A new proposal for diagnosis and structured reporting of COVID-19 on computed tomography imaging #MMPMID32558646
  • Gezer NS; Ergan B; Baris MM; Appak O; Sayiner AA; Balci P; Kuruuzum Z; Cavus SA; Kilinc O
  • Diagn Interv Radiol 2020[Jul]; 26 (4): 315-322 PMID32558646show ga
  • PURPOSE: Because of the widespread use of CT in the diagnosis of COVID 19, indeterminate presentations such as single, few or unilateral lesions amount to a considerable number. We aimed to develop a new classification and structured reporting system on CT imaging (COVID-19 S) that would facilitate the diagnosis of COVID-19 in the most accurate way. METHODS: Our retrospective cohort included 803 patients with a chest CT scan upon suspicion of COVID 19. The patients' history, physical examination, CT findings, RT PCR, and other laboratory test results were reviewed, and a final diagnosis was made as COVID 19 or non-COVID 19. Chest CT scans were classified according to the COVID 19 S CT diagnosis criteria. Cohen's kappa analysis was used. RESULTS: Final clinical diagnosis was COVID-19 in 98 patients (12%). According to the COVID-19 S CT diagnosis criteria, the number of patients in the normal, compatible with COVID 19, indeterminate and alternative diagnosis groups were 581 (72.3%), 97 (12.1%), 16 (2.0%) and 109 (13.6%). When the indeterminate group was combined with the group compatible with COVID 19, the sensitivity and specificity of COVID-19 S were 99.0% and 87.1%, with 85.8% positive predictive value (PPV) and 99.1% negative predictive value (NPV). When the indeterminate group was combined with the alternative diagnosis group, the sensitivity and specificity of COVID-19 S were 93.9% and 96.0%, with 94.8% PPV and 95.2% NPV. CONCLUSION: COVID-19 S CT classification system may meet the needs of radiologists in distinguishing COVID-19 from pneumonia of other etiologies and help optimize patient management and disease control in this pandemic by the use of structured reporting.
  • |Adult[MESH]
  • |Betacoronavirus/*genetics/isolation & purification[MESH]
  • |COVID-19[MESH]
  • |Cohort Studies[MESH]
  • |Coronavirus Infections/*diagnostic imaging/epidemiology/prevention & control/virology[MESH]
  • |Diagnosis, Differential[MESH]
  • |Diagnostic Tests, Routine/methods[MESH]
  • |Female[MESH]
  • |Humans[MESH]
  • |Male[MESH]
  • |Middle Aged[MESH]
  • |Pandemics/prevention & control[MESH]
  • |Pneumonia, Viral/*diagnostic imaging/epidemiology/prevention & control/virology[MESH]
  • |Pneumonia/*diagnostic imaging/etiology/pathology[MESH]
  • |Predictive Value of Tests[MESH]
  • |Radiologists/statistics & numerical data[MESH]
  • |Retrospective Studies[MESH]
  • |Reverse Transcriptase Polymerase Chain Reaction/methods[MESH]
  • |SARS-CoV-2[MESH]
  • |Sensitivity and Specificity[MESH]
  • |Thorax/*diagnostic imaging[MESH]
  • |Tomography, X-Ray Computed/*classification/methods[MESH]


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