The frequency and character of community-acquired pneumonia comparison before and during the COVID-19 epidemic in the multi-specialty hospital

Cover Page

Cite item

Full Text

Abstract

BACKGROUND: The 2019 coronavirus disease outbreak (COVID-19) quickly swept the world in just a month. Polymerase chain reaction (PCR) is used in the diagnosis of this disease, but this test has limitations related to false negative results, as well as PCR is a time-consuming procedure. Under these conditions, chest computed tomography (CT) can become one of the main methods in the Clinician’s Arsenal used for early detection of COVID-19 in patients who first seek medical help.

AIMS: comparison of the frequency of community-acquired pneumonia and its characteristics according to CT data before and during the COVID-19 epidemic and study of the possibilities of their timely detection and differential diagnosis.

MATERIALS AND METHODS: A retrospective analysis of chest CT scans results was performed in Davydovsky hospital (Moscow) from April 1 to April 17, 2020. It included all patients diagnosed with viral pneumonia at the CT. All patients with suspected diagnosis of viral pneumonia underwent PCR testing. Retrospective analysis of chest CT data from patients admitted to the hospital with suspected pneumonia for the same period in 2019 was taken as a comparison group.

RESULTS: For the period from April 1 to April 17, 2020 according to chest CT, pneumonia was diagnosed in 140 cases, of which 65 (46.4%) were described as viral, compared with the same period in 2019 − 7 diagnoses of viral pneumonia (10.3%) were described a significant increase in cases of viral pneumonia (5.723; p <0.01). Results of PCR test in patients with viral pneumonia according to CT data was: positive in 34 (52.3%), negative in 22 (33.8%), 9 (13.9%) patients were not tested. When comparing the frequency of detection on CT of viral pneumonia patterns in patients for the same period of time in 2019 and 2020, no significant differences were found. The probability of COVID-19 due to results of chest CT was: average 13.8%, high − 75.4%. The severity of viral pneumonia according to CT data was: light 38.5%, medium 46.2%, severe 12.3%, extremely severe 3.1%.

CONCLUSIONS: Rapid CT diagnostics of COVID-19, even with false negative results of PCR tests, can help to isolate a patient with suspected COVID-19, start treatment on time and prevent the further spread of viral infection in a pandemic. Nevertheless, due to the non-specificity of the revealed picture, the possibilities of CT to identify lung lesions by specific viral agents are limited.

About the authors

Stepan A. Yaremenko

State Moscow Clinical Hospital I.V.Davydovskiy; Lomonosov Moscow State University

Author for correspondence.
Email: yaremenkosa@yandex.ru
ORCID iD: 0000-0002-7709-977X

MD, PhD student

Russian Federation, Moscow

Natalia A. Rucheva

State Moscow Clinical Hospital I.V.Davydovskiy

Email: rna1969@yandex.ru
ORCID iD: 0000-0002-8063-4462

MD, PhD

Russian Federation, Moscow

Kirill N. Zhuravlev

State Moscow Clinical Hospital I.V.Davydovskiy

Email: kir232@mail.ru
ORCID iD: 0000-0003-1733-267X

MD

Russian Federation, Moscow

Valentin E. Sinitsyn

Lomonosov Moscow State University

Email: vsini@mail.ru
ORCID iD: 0000-0002-5649-2193

MD, PhD, Professor

Russian Federation, Moscow

References

  1. Zhu N, Zhang D, Wang W, et al. A novel coronavirus from patients with pneumonia in China, 2019. N Engl J Med. 2020;382(8):727–733. doi: 10.1056/NEJMoa2001017
  2. Xie X, Zhong Z, Zhao W, et al. Chest CT for Typical 2019-nCoV Pneumonia: Relationship to Negative RT-PCR Testing. Radiology. 2020;296(2):E41−E4. doi: 10.1148/radiol.2020200343
  3. World Health Organization. Summary of probable SARS cases with onset of illness from 1 November 2002 to 31 July 2003 (based on data as of December 31, 2003). Available from: https://www.who.int/publications/m/item/summary-of-probable-sars-cases-with-onset-of-illness-from-1-november-2002-to-31-july-2003
  4. World Health Organization. Naming the coronavirus disease (COVID-2019) and the virus that causes it. Available from: https://www.who.int/emergencies/diseases/novel-coronavirus-2019/technical-guidance/naming-the-coronavirus-disease-(covid-2019)-and-the-virus-that-causes-it
  5. She J, Jiang J, Ye L, et al. 2019 novel coronavirus of pneumonia in Wuhan, China: emerging attack and management strategies. Clin Transl Med. 2020;9(1):19. doi: 10.1186/s40169-020-00271-z
  6. Xu X, Chen P, Wang J, et al. Evolution of the novel coronavirus from the ongoing Wuhan outbreak and modeling of its spike protein for risk of human transmission. Sci China Life Sci. 2020;63(3):457–460. doi: 10.1007/s11427-020-1637-5
  7. Huang C, Wang Y, Li X, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020;395(10223):497–506. doi: 10.1016/S0140-6736(20)30183-5
  8. Fang Y, Zhang H, Xie J, et al. Sensitivity of Chest CT for COVID-19: Comparison to RT-PCR. Radiology. 2020; 296(2):E115−E117. doi: 10.1148/radiol.2020200432
  9. Chung M, Bernheim A, Mei X, et al. CT Imaging of the 2019 Novel Coronavirus (2019-nCoV) Pneumonia. Radiology. 2020. doi: 10.1148/radiol.2020200230
  10. BSTI. COVID-19 BSTI reporting templates and Codes. Available from: https://www.bsti.org.uk/covid-19-resources/covid-19-bsti-reporting-templates/
  11. Paul NS, Roberts H, Butany J, et al. Radiologic pattern of disease in patients with severe acute respiratory syndrome: The Toronto experience. Radiographics. 2004;24:553–563. doi: 10.1148/rg.242035193
  12. Das KM, Lee EY, Langer RD, Larsson SG. Middle East respiratory syndrome coronavirus: What does a radiologist need to know? AJR Am J Roentgenol. 2016;206(6):1193−1201. doi: 10.2214/AJR.15.15363
  13. Koo HJ, Lim S, Choe J, et al Radiographic and CT features of viral pneumonia. Radiographics. 2018;38(3):719−739. doi: 10.1148/rg.2018170048
  14. McGonagle D, Sharif K, O’Regan A, Bridgewood C. Interleukin-6 use in COVID-19 pneumonia related macrophage activation syndrome. Autoimmun Rev. 2020;102537. doi: 10.1016/j.autrev.2020.102537
  15. Colafrancesco S, Priori R, Alessandri C, et al. sCD163 in AOSD : a biomarker for macrophage activation related to hyperferritinemia. Immunol Res. 2014;60(2-3):177−183. doi: 10.1007/s12026-014-8563-7
  16. Wu C, Chen X, Cai Y, et al. Risk factors associated with acute respiratory distress syndrome and death in patients with coronavirus disease 2019 pneumonia in Wuhan, China. JAMA Intern Med. 2020;180(7):934−943. doi: 10.1001/jamainternmed.2020.0994

Supplementary files

Supplementary Files
Action
1. JATS XML
Download
2. Fig. 1. PCR testing results of patients with viral pneumonia diagnosed by computed tomography.

Download (48KB)
Indexing metadata
3. Fig. 3. Computed tomography of the chest organs; comparison of viral pneumonia images before and during the COVID-19 pandemic: a ― multiple subpleural sites of ground-glass opacity of the lung tissue (April 2019); b ― a similar presentation of an atypical pneumonia of viral origin (April 2020).

Download (264KB)
Indexing metadata
4. Fig. 4. Distribution of patients with a high and an average probability of COVID-19 according to the CT of the thoracic organs and depending on the disease severity.

Download (81KB)
Indexing metadata
5. Fig. 5. Viral pneumonia severity according to the computed tomography of the thoracic organs: a ― mild changes (CT-1), involvement of the lung parenchyma by ≤25%; b ― moderate changes (CT-2), involvement of the lung parenchyma by 25%–50%; c ― severe changes (CT-3), involvement of the lung parenchyma by 50%–75%; d ― extremely severe and critical changes (CT-4), involvement of the lung parenchyma by ≥75%.

Download (521KB)
Indexing metadata

Copyright (c) 2020 Yaremenko S.A., Rucheva N.A., Zhuravlev K.N., Sinitsyn V.E.

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

This website uses cookies

You consent to our cookies if you continue to use our website.

About Cookies