Статья

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

S. Yaremenko, N. Rucheva, K. Zhuravlev, V. Sinitsyn,
2020

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  

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  • 1. Version of Record от 2020-12-30

Метаданные

Об авторах
  • S. Yaremenko
    Moscow State University
  • N. Rucheva
    State Moscow Clinical Hospital I.V.Davydovskiy
  • K. Zhuravlev
    State Moscow Clinical Hospital I.V.Davydovskiy
  • V. Sinitsyn
    Moscow State University
Предметная рубрика
  • COVID-19
Название журнала
  • Digital Diagnostics
Том
  • 1
Выпуск
  • 1
Страницы
  • 37-47
Тип документа
  • journal article
Источник
  • lens