• J Thorac Imaging · Jan 2021

    Performance of Chest Computed Tomography in Differentiating Coronavirus Disease 2019 From Other Viral Infections Using a Standardized Classification.

    • Borges da Silva TelesGustavoGHospital Israelita Albert Einstein.United Health Group., Kaiser Ururahy Nunes FonsecaEduardoEHospital Israelita Albert Einstein.Heart Institute - University of São Paulo., Patricia Yokoo, Marques Almeida SilvaMuriloMHospital Israelita Albert Einstein., Elaine Yanata, Hamilton Shoji, Rodrigo Bastos Duarte Passos, Caruso ChateRodrigoRHospital Israelita Albert Einstein.Heart Institute - University of São Paulo., and Gilberto Szarf.
    • Hospital Israelita Albert Einstein.
    • J Thorac Imaging. 2021 Jan 1; 36 (1): 31-36.

    BackgroundAn expert consensus recently proposed a standardized coronavirus disease 2019 (COVID-19) reporting language for computed tomography (CT) findings of COVID-19 pneumonia.PurposeThe purpose of the study was to evaluate the performance of CT in differentiating COVID-19 from other viral infections using a standardized reporting classification.MethodsA total of 175 consecutive patients were retrospectively identified from a single tertiary-care medical center from March 15 to March 24, 2020, including 87 with positive reverse transcription-polymerase chain reaction (RT-PCR) test for COVID-19 and 88 with negative COVID-19 RT-PCR test, but positive respiratory pathogen panel. Two thoracic radiologists, who were blinded to RT-PCR and respiratory pathogen panel results, reviewed chest CT images independently and classified the imaging findings under 4 categories: "typical" appearance, "indeterminate," "atypical," and "negative" for pneumonia. The final classification was based on consensus between the readers.ResultsPatients with COVID-19 were older than patients with other viral infections (P=0.038). The inter-rater agreement of CT categories between the readers ranged from good to excellent, κ=0.80 (0.73 to 0.87). Final CT categories were statistically different among COVID-19 and non-COVID-19 groups (P<0.001). CT "typical" appearance was more prevalent in the COVID-19 group (64/87, 73.6%) than in the non-COVID-19 group (2/88, 2.3%). When considering CT "typical" appearance as a positive test, a sensitivity of 73.6% (95% confidence interval [CI]: 63%-82.4%), specificity of 97.7% (95% CI: 92%-99.7%), positive predictive value of 97% (95% CI: 89.5%-99.6%), and negative predictive value of 78.9% (95% CI: 70%-86.1%) were observed.ConclusionThe standardized chest CT classification demonstrated high specificity and positive predictive value in differentiating COVID-19 from other viral infections when presenting a "typical" appearance in a high pretest probability environment. Good to excellent inter-rater agreement was found regarding the CT standardized categories between the readers.

      Pubmed     Full text   Copy Citation     Plaintext  

      Add institutional full text...

    Notes

     
    Knowledge, pearl, summary or comment to share?
    300 characters remaining
    help        
    You can also include formatting, links, images and footnotes in your notes
    • Simple formatting can be added to notes, such as *italics*, _underline_ or **bold**.
    • Superscript can be denoted by <sup>text</sup> and subscript <sub>text</sub>.
    • Numbered or bulleted lists can be created using either numbered lines 1. 2. 3., hyphens - or asterisks *.
    • Links can be included with: [my link to pubmed](http://pubmed.com)
    • Images can be included with: ![alt text](https://bestmedicaljournal.com/study_graph.jpg "Image Title Text")
    • For footnotes use [^1](This is a footnote.) inline.
    • Or use an inline reference [^1] to refer to a longer footnote elseweher in the document [^1]: This is a long footnote..

    hide…

What will the 'Medical Journal of You' look like?

Start your free 21 day trial now.

We guarantee your privacy. Your email address will not be shared.