WU Jianguo, LUO Jianfei, LIU Jiasheng, LIU Dan, DENG Jun, QIAN Zhicheng, HU Liping, LI Shijun, XIAO Zhe, WANG Xufeng, PENG Zhiyang, YAN Ruicheng. Detection of 2019-nCoV by real-time RT-PCR using multiple biological samples in severe/critically ill patients[J]. ACADEMIC JOURNAL OF CHINESE PLA MEDICAL SCHOOL, 2020, 41(3): 205-207, 211. DOI: 10.3969/j.issn.2095-5227.2020.03.001
Citation: WU Jianguo, LUO Jianfei, LIU Jiasheng, LIU Dan, DENG Jun, QIAN Zhicheng, HU Liping, LI Shijun, XIAO Zhe, WANG Xufeng, PENG Zhiyang, YAN Ruicheng. Detection of 2019-nCoV by real-time RT-PCR using multiple biological samples in severe/critically ill patients[J]. ACADEMIC JOURNAL OF CHINESE PLA MEDICAL SCHOOL, 2020, 41(3): 205-207, 211. DOI: 10.3969/j.issn.2095-5227.2020.03.001

Detection of 2019-nCoV by real-time RT-PCR using multiple biological samples in severe/critically ill patients

  •   Objective  To analyze the positive rates of 2019-nCoV by real-time RT-PCR using various biological samples in severe/critically ill patients, and explore their clinical significance.
      Methods  The confirmed severe/critically ill cases of COVID-19 in the fifth ward of Renmin Hospital of Wuhan University from January 31 to February 19 in 2020 were tested for 2019-nCoV by real-time fluorescence reverse transcriptase polymerase chain reaction. Positive rates of different specimens including nasopharyngeal swabs, sputum, blood, feces and anal swabs were compared.
      Results  A total of 19 severe/critically ill COVID-19 cases were included. After two weeks' treatment, positive rate of 2019-nCoV in the nasopharyngeal swab specimens was 42.10% (8/19), and it was 68.42% (13/19) in the sputum, 5.26% (1/19) in the blood, 21.05% (4/19) in the feces, 10.52% (2/19) in the anal swab.
      Conclusion  The positive rate of 2019-nCoV nucleic acid from sputum specimens of severe/critical ill COVID-19 patients is higher than that of nasopharyngeal swabs, blood and fecal/anal swabs. The detection using multiple biological samples can increase the detection rate of 2019-nCoV infection and reduce the false negative rate in discharged cases.
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