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Analysis of 394 COVID-19 cases infected with Omicron variant in Shenzhen: impact of underlying diseases to patient's symptoms.
Zhang, Peiyan; Cai, Zhao; He, Zhiguang; Chen, Peifen; Wu, Weibo; Lin, Yuanlong; Feng, Shiyan; Peng, Ling; Li, Jianming; Yuan, Jing; Yang, Liang; Wang, Fuxiang; Liu, Yingxia; Lu, Hongzhou.
  • Zhang P; Department of Infectious Diseases, Shenzhen Third People's Hospital, Second Hospital Affiliated to Southern University of Science and Technology, Shenzhen, 518112, China.
  • Cai Z; School of Medicine, Southern University of Science and Technology, Shenzhen, 518055, China.
  • He Z; Luohu Clinical Institute of Shantou University Medical College, Shantou, China.
  • Chen P; Department of Infectious Diseases, Shenzhen Third People's Hospital, Second Hospital Affiliated to Southern University of Science and Technology, Shenzhen, 518112, China.
  • Wu W; Department of Infectious Diseases, Shenzhen Third People's Hospital, Second Hospital Affiliated to Southern University of Science and Technology, Shenzhen, 518112, China.
  • Lin Y; Department of Infectious Diseases, Shenzhen Third People's Hospital, Second Hospital Affiliated to Southern University of Science and Technology, Shenzhen, 518112, China.
  • Feng S; Department of Infectious Diseases, Shenzhen Third People's Hospital, Second Hospital Affiliated to Southern University of Science and Technology, Shenzhen, 518112, China.
  • Peng L; Department of Infectious Diseases, Shenzhen Third People's Hospital, Second Hospital Affiliated to Southern University of Science and Technology, Shenzhen, 518112, China.
  • Li J; Department of Infectious Diseases, Shenzhen Third People's Hospital, Second Hospital Affiliated to Southern University of Science and Technology, Shenzhen, 518112, China.
  • Yuan J; Department of Infectious Diseases, Shenzhen Third People's Hospital, Second Hospital Affiliated to Southern University of Science and Technology, Shenzhen, 518112, China.
  • Yang L; School of Medicine, Southern University of Science and Technology, Shenzhen, 518055, China. yangl@sustech.edu.cn.
  • Wang F; National Clinical Research Center for Infectious Disease, Shenzhen, 518112, China. yangl@sustech.edu.cn.
  • Liu Y; Shenzhen Key Laboratory for Gene Regulation and Systems Biology, Southern University of Science and Technology, Shenzhen, 518055, China. yangl@sustech.edu.cn.
  • Lu H; Department of Infectious Diseases, Shenzhen Third People's Hospital, Second Hospital Affiliated to Southern University of Science and Technology, Shenzhen, 518112, China. 13927486077@163.com.
Eur J Med Res ; 27(1): 291, 2022 Dec 15.
Article in English | MEDLINE | ID: covidwho-2162426
ABSTRACT

OBJECTIVES:

The emergence of new variants of SARS-CoV-2 is continuously posing pressure to the epidemic prevention and control in China. The Omicron variant of SARS-CoV-2 having stronger infectivity, immune escape ability, and capability causing repetitive infection spread to many countries and regions all over the world including South Africa, United States and United Kingdom etc., in a short time. The outbreaks of Omicron variant also occurred in China. The aim of this study is to understand the epidemiological characteristics of Omicron variant infection in Shenzhen and to provide scientific basis for effective disease control and prevention.

METHODS:

The clinical data of 394 imported COVID-19 cases infected with Omicron variant from 16 December 2021 to 24 March 2022 admitted to the Third People's hospital of Shenzhen were collected and analyzed retrospectively. Nucleic acid of SARS-CoV-2 of nasopharyngeal swabs and blood samples was detected using 2019-nCoV nucleic acid detection kit. Differences in Ct values of N gene were compared between mild group and moderate group. The specific IgG antibody was detected using 2019-nCoV IgG antibody detection kit. Statistical analysis was done using SPSS software and graphpad prism.

RESULTS:

Patients were categorized into mild group and moderate group according to disease severity. The data on the general conditions, underlying diseases, COVID-19 vaccination and IgG antibody, viral load, laboratory examination results, and duration of hospitalization, etc., were compared among disease groups. Mild gorup had higher IgG level and shorter nucleic acid conversion time. Patients with underlying diseases have 4.6 times higher probability to progress to moderate infection.

CONCLUSION:

In terms of epidemic prevention, immunization coverage should be strengthened in the population with underlying diseases. In medical institutions, more attention needs to be paid to such vulnerable population and prevent further deterioration of the disease.
Keywords

Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Topics: Vaccines / Variants Language: English Journal: Eur J Med Res Journal subject: Medicine Year: 2022 Document Type: Article Affiliation country: S40001-022-00927-1

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Topics: Vaccines / Variants Language: English Journal: Eur J Med Res Journal subject: Medicine Year: 2022 Document Type: Article Affiliation country: S40001-022-00927-1