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Yuan R, Chen H, Yi L, Li X, Hu X, Li X, Zhang H, Zhou P, Liang C, Lin H, Zeng L, Zhuang X, Ruan Q, Chen Y, Deng Y, Liu Z, Lu J, Xiao J, Chen L, Xiao X, Li J, Li B, Li Y, He J, Sun J. Enhanced immunity against SARS-CoV-2 in returning Chinese individuals. Hum Vaccin Immunother 2024; 20:2300208. [PMID: 38191194 DOI: 10.1080/21645515.2023.2300208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Accepted: 12/26/2023] [Indexed: 01/10/2024] Open
Abstract
Global COVID-19 vaccination programs effectively contained the fast spread of SARS-CoV-2. Characterizing the immunity status of returned populations will favor understanding the achievement of herd immunity and long-term management of COVID-19 in China. Individuals were recruited from 7 quarantine stations in Guangzhou, China. Blood and throat swab specimens were collected from participants, and their immunity status was determined through competitive ELISA, microneutralization assay and enzyme-linked FluoroSpot assay. A total of 272 subjects were involved in the questionnaire survey, of whom 235 (86.4%) were returning Chinese individuals and 37 (13.6%) were foreigners. Blood and throat swab specimens were collected from 108 returning Chinese individuals. Neutralizing antibodies against SARS-CoV-2 were detected in ~90% of returning Chinese individuals, either in the primary or the homologous and heterologous booster vaccination group. The serum NAb titers were significantly decreased against SARS-CoV-2 Omicron BA.5, BF.7, BQ.1 and XBB.1 compared with the prototype virus. However, memory T-cell responses, including specific IFN-γ and IL-2 responses, were not different in either group. Smoking, alcohol consumption, SARS-CoV-2 infection, COVID-19 vaccination, and the time interval between last vaccination and sampling were independent influencing factors for NAb titers against prototype SARS-CoV-2 and variants of concern. The vaccine dose was the unique common influencing factor for Omicron subvariants. Enhanced immunity against SARS-CoV-2 was established in returning Chinese individuals who were exposed to reinfection and vaccination. Domestic residents will benefit from booster homologous or heterologous COVID-19 vaccination after reopening of China, which is also useful against breakthrough infection.
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Affiliation(s)
- Runyu Yuan
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Huimin Chen
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
| | - Lina Yi
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Xinxin Li
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
| | - Ximing Hu
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
- School of Public Health, Southern Medical University, Guangzhou, China
| | - Xing Li
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Huan Zhang
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Pingping Zhou
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Chumin Liang
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Huifang Lin
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Lilian Zeng
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Xue Zhuang
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - QianQian Ruan
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
- School of Public Health, Sun Yat-Sen University, Guangzhou, China
| | - Yueling Chen
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
- School of Public Health, Guangdong Pharmaceutical University, Guangzhou, China
| | - Yingyin Deng
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
- School of Public Health, Southern Medical University, Guangzhou, China
| | - Zhe Liu
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Jing Lu
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Jianpeng Xiao
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Liang Chen
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Xincai Xiao
- Guangzhou Chest Hospital, Guangzhou Medical University, Guangzhou, China
| | - Jing Li
- Quality Control Department, Sinovac Life Sciences Co. Ltd., Beijing, China
| | - Baisheng Li
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Yan Li
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Jianfeng He
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Jiufeng Sun
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
- School of Public Health, Southern Medical University, Guangzhou, China
- School of Public Health, Sun Yat-Sen University, Guangzhou, China
- School of Public Health, Guangdong Pharmaceutical University, Guangzhou, China
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Zhang Q, Jiao L, Chen Q, Bulstra CA, Geldsetzer P, de Oliveira T, Yang J, Wang C, Bärnighausen T, Chen S. COVID-19 antibody responses in individuals with natural immunity and with vaccination-induced immunity: a systematic review and meta-analysis. Syst Rev 2024; 13:189. [PMID: 39030630 PMCID: PMC11264703 DOI: 10.1186/s13643-024-02597-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Accepted: 06/26/2024] [Indexed: 07/21/2024] Open
Abstract
BACKGROUND The COVID-19 pandemic has caused a large mortality and morbidity burden globally. For individuals, a strong immune response is the most effective means to block SARS-CoV-2 infection. To inform clinical case management of COVID-19, development of improved vaccines, and public health policy, a better understanding of antibody response dynamics and duration following SARS-CoV-2 infection and after vaccination is imperatively needed. METHODS We systematically analyzed antibody response rates in naturally infected COVID-19 patients and vaccinated individuals. Specifically, we searched all published and pre-published literature between 1 December 2019 and 31 July 2023 using MeSH terms and "all field" terms comprising "COVID-19" or "SARS-CoV-2," and "antibody response" or "immunity response" or "humoral immune." We included experimental and observational studies that provided antibody positivity rates following natural COVID-19 infection or vaccination. A total of 44 studies reporting antibody positivity rate changes over time were included. RESULTS The meta-analysis showed that within the first week after COVID-19 symptom onset/diagnosis or vaccination, antibody response rates in vaccinated individuals were lower than those in infected patients (p < 0.01), but no significant difference was observed from the second week to the sixth month. IgG, IgA, and IgM positivity rates increased during the first 3 weeks; thereafter, IgG positivity rates were maintained at a relatively high level, while the IgM seroconversion rate dropped. CONCLUSIONS Antibody production following vaccination might not occur as quickly or strongly as after natural infection, and the IgM antibody response was less persistent than the IgG response.
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Affiliation(s)
- Qiuying Zhang
- Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Lirui Jiao
- Department of Health Policy and Management, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Qiushi Chen
- The Harold and Inge Marcus Department of Industrial and Manufacturing Engineering, The Pennsylvania State University, University Park, PA, USA
| | - Caroline A Bulstra
- Heidelberg Institute of Global Health, Faculty of Medicine and University Hospital, Heidelberg University, Im Neuenheimer Feld 130/3, Heidelberg, 69120, Germany
- Department of Public Health, Erasmus University Medical Center, Rotterdam, Netherlands
- Health Systems Innovation Lab, Harvard T.H. Chan School of Public Health, Harvard University, Cambridge, USA
| | - Pascal Geldsetzer
- Division of Primary Care and Population Health, Stanford University, Stanford, CA, USA
- Chan Zuckerberg Biohub, San Francisco, CA, USA
| | - Tulio de Oliveira
- KwaZulu-Natal Research Innovation and Sequencing Platform, University of KwaZulu-Natal, Durban, South Africa
- Center for the AIDS Program of Research in South Africa (CAPRISA), Durban, South Africa
| | - Juntao Yang
- Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Chen Wang
- Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
| | - Till Bärnighausen
- Heidelberg Institute of Global Health, Faculty of Medicine and University Hospital, Heidelberg University, Im Neuenheimer Feld 130/3, Heidelberg, 69120, Germany
| | - Simiao Chen
- Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
- Heidelberg Institute of Global Health, Faculty of Medicine and University Hospital, Heidelberg University, Im Neuenheimer Feld 130/3, Heidelberg, 69120, Germany.
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Li H, Wang X, Wang S, Feng X, Wang L, Li Y. Acceptance, safety, and immunogenicity of a booster dose of inactivated SARS-CoV-2 vaccine in patients with primary biliary cholangitis. Heliyon 2024; 10:e28405. [PMID: 38560178 PMCID: PMC10981126 DOI: 10.1016/j.heliyon.2024.e28405] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2023] [Revised: 03/18/2024] [Accepted: 03/18/2024] [Indexed: 04/04/2024] Open
Abstract
Inactivated coronavirus disease 2019 (COVID-19) vaccines showed impaired immunogenicity in some autoimmune diseases, but it remains unclear in primary biliary cholangitis (PBC). This study aimed to explore the antibody response to the inactivated COVID-19 vaccine in individuals with PBC, as well as to evaluate coverage, safety, and attitudes toward the COVID-19 vaccine among them. Two cohorts of patients with PBC were enrolled in this study. One cohort was arranged to evaluate the immunogenicity of the inactivated COVID-19 vaccine, another cohort participated in an online survey. The titers of the anti-receptor-binding domain (RBD)-specific immunoglobulin G (IgG), neutralizing antibody (NAb) toward severe acute respiratory syndrome coronavirus 2 wild-type, and NAb toward Omicron BA.4/5 subvariants were detected to assess antibody response from the vaccine. After booster vaccination for more than six months, patients with PBC had significantly lowered levels of anti-RBD-specific IgG compared to HCs, and the inhibition rates of NAb toward wild-type also declined in individuals with PBC. The detected levels of NAb toward Omicron BA.4/5 were below the positive threshold in patients with PBC and HCs. Laboratory parameters did not significantly correlate with any of the three antibodies. The online survey revealed that 24% of patients with PBC received three COVID-19 vaccines, while 63% were unimmunized. Adverse effect rates after the first, second, and third vaccine doses were 6.1%, 10.3%, and 9.5%, respectively. Unvaccinated patients with PBC were more worried about the safety of the vaccine than those who were vaccinated (P = 0.004). As a result, this study fills the immunological assessment gap in patients with PBC who received inactivated COVID-19 vaccines.
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Affiliation(s)
- Haolong Li
- Department of Clinical Laboratory, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China
| | - Xu Wang
- Department of Rheumatology, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China
| | - Siyu Wang
- Department of Clinical Laboratory, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China
| | - Xinxin Feng
- Department of Clinical Laboratory, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China
| | - Li Wang
- Department of Rheumatology, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China
| | - Yongzhe Li
- Department of Clinical Laboratory, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China
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Liu Y, Yuan W, Zhan H, Kang H, Li X, Chen Y, Li H, Sun X, Cheng L, Zheng H, Wang W, Guo X, Li Y, Dai E. SARS-CoV-2 Vaccine Uptake among Patients with Chronic Liver Disease: A Cross-Sectional Analysis in Hebei Province, China. Vaccines (Basel) 2023; 11:1293. [PMID: 37631861 PMCID: PMC10458449 DOI: 10.3390/vaccines11081293] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Revised: 07/15/2023] [Accepted: 07/26/2023] [Indexed: 08/27/2023] Open
Abstract
Chronic liver disease (CLD) patients have higher mortality and hospitalization rates after infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This study aimed to explore SARS-CoV-2 vaccine perceptions, side effects, factors associated with nonvaccination and attitudes toward fourth-dose vaccine among CLD patients. The differences between vaccinated and unvaccinated groups among 1491 CLD patients and the risk factors associated with nonvaccination status were analyzed. In total, 1239 CLD patients were immunized against SARS-CoV-2. CLD patients have a high level of trust in the government and clinicians and were likely to follow their recommendations for vaccination. Reasons reported for nonvaccination were mainly concerns about the vaccines affecting their ongoing treatments and the fear of adverse events. However, only 4.84% of patients reported mild side effects. Risk factors influencing nonvaccination included being older in age, having cirrhosis, receiving treatments, having no knowledge of SARS-CoV-2 vaccine considerations and not receiving doctors' positive advice on vaccination. Furthermore, 20.6% of completely vaccinated participants refused the fourth dose because they were concerned about side effects and believed that the complete vaccine was sufficiently protective. Our study proved that SARS-CoV-2 vaccines were safe for CLD patients. Our findings suggest that governments and health workers should provide more SARS-CoV-2 vaccination information and customize strategies to improve vaccination coverage and enhance vaccine protection among the CLD population.
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Affiliation(s)
- Yongmei Liu
- Department of Clinical Laboratory, State Key Laboratory of Complex, Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing 100730, China; (Y.L.); (H.Z.); (X.L.); (H.L.); (L.C.)
| | - Wenfang Yuan
- Division of Liver Diseases, The Fifth Hospital of Shijiazhuang, Hebei Medical University, Shijiazhuang 050021, China; (W.Y.); (H.K.); (Y.C.); (X.S.); (H.Z.); (W.W.); (X.G.)
| | - Haoting Zhan
- Department of Clinical Laboratory, State Key Laboratory of Complex, Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing 100730, China; (Y.L.); (H.Z.); (X.L.); (H.L.); (L.C.)
| | - Haiyan Kang
- Division of Liver Diseases, The Fifth Hospital of Shijiazhuang, Hebei Medical University, Shijiazhuang 050021, China; (W.Y.); (H.K.); (Y.C.); (X.S.); (H.Z.); (W.W.); (X.G.)
| | - Xiaomeng Li
- Department of Clinical Laboratory, State Key Laboratory of Complex, Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing 100730, China; (Y.L.); (H.Z.); (X.L.); (H.L.); (L.C.)
- Department of Clinical Laboratory, Peking University People’s Hospital, Beijing 100035, China
| | - Yongliang Chen
- Division of Liver Diseases, The Fifth Hospital of Shijiazhuang, Hebei Medical University, Shijiazhuang 050021, China; (W.Y.); (H.K.); (Y.C.); (X.S.); (H.Z.); (W.W.); (X.G.)
| | - Haolong Li
- Department of Clinical Laboratory, State Key Laboratory of Complex, Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing 100730, China; (Y.L.); (H.Z.); (X.L.); (H.L.); (L.C.)
| | - Xingli Sun
- Division of Liver Diseases, The Fifth Hospital of Shijiazhuang, Hebei Medical University, Shijiazhuang 050021, China; (W.Y.); (H.K.); (Y.C.); (X.S.); (H.Z.); (W.W.); (X.G.)
| | - Linlin Cheng
- Department of Clinical Laboratory, State Key Laboratory of Complex, Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing 100730, China; (Y.L.); (H.Z.); (X.L.); (H.L.); (L.C.)
| | - Haojie Zheng
- Division of Liver Diseases, The Fifth Hospital of Shijiazhuang, Hebei Medical University, Shijiazhuang 050021, China; (W.Y.); (H.K.); (Y.C.); (X.S.); (H.Z.); (W.W.); (X.G.)
| | - Wei Wang
- Division of Liver Diseases, The Fifth Hospital of Shijiazhuang, Hebei Medical University, Shijiazhuang 050021, China; (W.Y.); (H.K.); (Y.C.); (X.S.); (H.Z.); (W.W.); (X.G.)
| | - Xinru Guo
- Division of Liver Diseases, The Fifth Hospital of Shijiazhuang, Hebei Medical University, Shijiazhuang 050021, China; (W.Y.); (H.K.); (Y.C.); (X.S.); (H.Z.); (W.W.); (X.G.)
| | - Yongzhe Li
- Department of Clinical Laboratory, State Key Laboratory of Complex, Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing 100730, China; (Y.L.); (H.Z.); (X.L.); (H.L.); (L.C.)
| | - Erhei Dai
- Division of Liver Diseases, The Fifth Hospital of Shijiazhuang, Hebei Medical University, Shijiazhuang 050021, China; (W.Y.); (H.K.); (Y.C.); (X.S.); (H.Z.); (W.W.); (X.G.)
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Dong Y, Luo S, Wang Y, Shi Y. Retrospective analysis of COVID-19 among 391 hospitalized patients in the Henan province of China. Medicine (Baltimore) 2023; 102:e34325. [PMID: 37478231 PMCID: PMC10662902 DOI: 10.1097/md.0000000000034325] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Accepted: 06/22/2023] [Indexed: 07/23/2023] Open
Abstract
This study investigated the clinical characteristics and risk factors of coronavirus disease 2019 (COVID-19) in patients in designated hospitals (Port Hospital) in the Henan province. A total of 391 COVID-19 patients with complete case information from August 6, 2021 to February 26, 2022 were selected. Logistic regression was used to analyze the differences between the clinical types, ages, and sex of the patients. Multivariate regression analysis of the severe group indicated that underlying diseases [odds ratio (OR):6.76, 95% confidence interval (CI):1.83-24.93], increased urea levels (OR: 1.41, 95% CI: 1.04-1.91), old age (OR: 1.05, 95% CI: 1.00-1.10), and increased lactic dehydrogenase (OR: 1.02, 95% CI: 1.01-1.03) levels and decreased hemoglobin (OR: 0.95, 95% CI: 0.91-1.00) levels were predictors of illness severity. Multivariate regression analysis for those > 50 years of age showed that underlying diseases (OR: 7.06, 95% CI: 2.79-17.89) and increased urea (OR: 1.91, 95% CI: 1.47-2.48), total bilirubin (OR: 1.14, 95% CI: 1.08-1.21), total protein (OR: 1.08, 95% CI: 1.00-1.17), and lactic dehydrogenase (OR: 1.01, 95% CI: 1.00-1.02) levels and decreased albumin (OR: 0.66, 95% CI: 0.58-0.76) levels were characteristics of COVID-19. Multivariate regression analysis stratified by sex showed that the characteristics of COVID-19 patients were increased white blood cell count in males (OR: 0.66, 95% CI: 0.55-0.78) as well as increased creatinine levels (OR: 0.89, 95% CI: 0.87-0.91). This retrospective analysis provides useful information to support the clinical management of patients with COVID-19.
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Affiliation(s)
- Yang Dong
- Department of Clinical Pathology, Henan Provincial People's Hospital, Department of Clinical Pathology of Central China Fuwai Hospital, Central China Fuwai Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Suyan Luo
- Department of Clinical Microbiology, The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yali Wang
- Department of Clinical Microbiology, Henan Provincial Chest Hospital, Zhengzhou, China
| | - Yujie Shi
- Department of Clinical Pathology, Henan Provincial People's Hospital, Department of Clinical Pathology of Central China Fuwai Hospital, Central China Fuwai Hospital of Zhengzhou University, Zhengzhou, Henan, China
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