Analysis of the Factors Associated with Negative Conversion of Severe Acute Respiratory Syndrome Coronavirus 2 RNA of Coronavirus Disease 2019

Authors

  • Nan Jiang Department of Emergency, China-Japan Union Hospital, Jilin University, Changchun, China
  • Yang Liu Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, China
  • Bo Yang Institute of Organ Transplantation, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
  • Zhijun Li Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, China
  • Daoyuan Si Department of Cardiology, China-Japan Union Hospital, Jilin University, Changchun, China
  • Piyong Ma Department of Critical Care Unit, China-Japan Union Hospital, Jilin University, Changchun, China
  • Jinnan Zhang Department of Neurosurgery, China-Japan Union Hospital, Jilin University, Changchun, China
  • Tianji Liu Department of Emergency, China-Japan Union Hospital, Jilin University, Changchun, China
  • Qiong Yu Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, China http://orcid.org/0000-0003-1143-1749

DOI:

https://doi.org/10.3889/oamjms.2020.5488

Keywords:

SARS-CoV-2,Risk Factor, Cox Regression, Negative Conversion

Abstract

AIM: To understand the factors associated with negative conversion of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA, targeted surveillance and control measures can be taken to provide scientific basis for the treatment of the disease and to improve the prognosis of the disease.

METHODS: Using the method of retrospective cohort study, we collected the data of Coronavirus Disease 2019 (COVID-19) patients in Tongji Hospital of Wuhan, China from 10 January to 25 March, 2020. Among the data of 282 cases, 271 patients, according to whether the negative conversion happened, were divided into negative conversion group and control group. We made the quantitative variables into classification; Chi-square test single-factor and Cox regression were used in univariate analysis and extracted 30 meaningful variables, then through the collinearity diagnosis, excluded the existence of collinear variables. Finally, 22 variables were included in Cox regression analysis.

RESULTS: The gender distribution was statistically significant between two groups (p < 0.05). While in the negative conversion group, the patients of non-severe group occupied a large proportion (p < 0.001). The median time for the negative conversion group was 17 days, and at the end of the observation period, the virus duration in control group was 24 days (p < 0.05). A total of 55 variables were included in univariate analysis, among which 30 variables were statistically different between the two groups. After screening variables through collinearity diagnosis, 22 variables were included in the Cox regression analysis. Last, lactate dehydrogenase (LDH), age, fibrinogen (FIB), and disease severity were associated with negative conversion of SARS-CoV-2 RNA.

CONCLUSION: Our results suggest that in the treatment of COVID-19, focus on the age of more than 65 years old, severe, high level of LDH, FIB patients, and take some targeted treatment, such as controlling of inflammation, reducing organ damage, so as to provide good conditions for virus clearance in the body.

Downloads

Download data is not yet available.

Metrics

Metrics Loading ...

Plum Analytics Artifact Widget Block

References

Zhu N, Zhang D, Wang W, Li X, Yang B, Song J, et al. A Novel coronavirus from patients with pneumonia in China, 2019. N Engl J Med. 2020;382(8):727-33. https://doi.org/10.1056/NEJMoa2001017 PMid: 31978945 DOI: https://doi.org/10.1056/NEJMoa2001017

Shi Y, Wang G, Cai XP, Deng JW, Zheng L, Zhu HH, et al. An overview of COVID-19. J Zhejiang Univ Sci B. 2020;21(5):343- 60. https://doi.org/10.1631/jzus.B2000083 PMid: 32425000 DOI: https://doi.org/10.1631/jzus.B2000083

Zhai P, Ding Y, Wu X, Long J, Zhong Y, Li Y. The epidemiology, diagnosis and treatment of COVID-19. Int J Antimicrob Agents. 2020;55(5):105955. https://doi.org/10.1016/j.ijantimicag.2020.105955 PMid: 32234468 DOI: https://doi.org/10.1016/j.ijantimicag.2020.105955

Vankadari N, Wilce JA. Emerging WuHan (COVID-19) coronavirus: Glycan shield and structure prediction of spike glycoprotein and its interaction with human CD26. Emerg Microbes Infect. 2020;9(1):601-4. https://doi.org/10.1080/2222 1751.2020.1739565 PMid:32178593 DOI: https://doi.org/10.1080/22221751.2020.1739565

Fu Y, Han P, Zhu R, Bai T, Yi J, Zhao X, et al. Risk factors for viral RNA shedding in COVID-19 patients. Eur Respir J. 2020;56(1):2001190. https://doi.org/10.1183/13993003.01190-2020 PMid:32398298 DOI: https://doi.org/10.1183/13993003.01190-2020

Yan Y, Yang Y, Wang F, Ren H, Zhang S, Shi X, et al. Clinical characteristics and outcomes of patients with severe covid-19 with diabetes. BMJ Open Diabetes Res Care. 2020;8(1):1343. https://doi.org/10.1136/bmjdrc-2020-001343 PMid:32345579 DOI: https://doi.org/10.1136/bmjdrc-2020-001343

Magro G. SARS-CoV-2 and COVID-19: Is interleukin-6 (IL- 6) the “culprit lesion” of ARDS onset? What is there besides tocilizumab? SGP130Fc. Cytokine X. 2020;14:100029. https://doi.org/10.1016/j.cytox.2020.100029 PMid:32421092 DOI: https://doi.org/10.1016/j.cytox.2020.100029

Wang F, Yang Y, Dong K, Yan Y, Zhang S, Ren H, et al. Clinical characteristics of 28 patients with diabetes and covid-19 in Wuhan, China. Endocr Pract. 2020;26(6):668-74. https://doi.org/10.4158/EP-2020-0108 PMid: 32357072 DOI: https://doi.org/10.4158/EP-2020-0108

Liu B, Li M, Zhou Z, Guan X, Xiang Y. Can we use interleukin-6 (IL-6) blockade for coronavirus disease 2019 (COVID-19)- induced cytokine release syndrome (CRS)? J Autoimmun. 2020;111:102452. https://doi.org/10.1016/j.jaut.2020.102452 PMid:32291137 DOI: https://doi.org/10.1016/j.jaut.2020.102452

Arnaldez FI, O’Day SJ, Drake CG, Fox BA, Fu B, Urba WJ, et al. The society for immunotherapy of cancer perspective on regulation of interleukin-6 signaling in COVID-19-related systemic inflammatory response. J Immunother Cancer. 2020;8(1):930. https://doi.org/10.1136/jitc-2020-000930 PMid:32385146 DOI: https://doi.org/10.1136/jitc-2020-000930

Lagunas-Rangel FA, Chávez-Valencia V. High IL-6/IFN-γ ratio could be associated with severe disease in COVID-19 patients. J Med Virol. 2020;10:25900. https://doi.org/10.1002/jmv.25900 PMid:32297995 DOI: https://doi.org/10.1002/jmv.25900

Zhang X, Tan Y, Ling Y, Lu G, Liu F, Yi Z, et al. Viral and host factors related to the clinical outcome of COVID-19. Nature. 2020;583(7816):437-40. https://doi.org/10.1038/s41586-020-2355-0 PMid:32434211 DOI: https://doi.org/10.1038/s41586-020-2355-0

Gebhard C, Regitz-Zagrosek V, Neuhauser HK, Morgan R, Klein SL. Impact of sex and gender on COVID-19 outcomes in Europe. Biol Sex Differ. 2020;11(1):29. https://doi.org/10.1186/s13293-020-00304-9 PMid:32450906 DOI: https://doi.org/10.1186/s13293-020-00304-9

Penna C, Mercurio V, Tocchetti CG, Pagliaro P. Sex-related differences in COVID-19 lethality. Br J Pharmacol. 2020;177(19):4375-85. https://doi.org/10.1111/bph.15207 PMid:32698249 DOI: https://doi.org/10.1111/bph.15207

Dana PM, Sadoughi F, Hallajzadeh J, Asemi Z, Mansournia MA, Yousefi B, et al. An insight into the sex differences in COVID-19 patients: What are the possible causes? Prehosp Disaster Med. 2020;35(4):438-41. https://doi.org/10.1017/S1049023X20000837 PMid:32600476 DOI: https://doi.org/10.1017/S1049023X20000837

Hu X, Xing Y, Jia J, Ni W, Liang J, Zhao D, et al. Factors associated with negative conversion of viral RNA in patients hospitalized with COVID-19. Sci Total Environ. 2020;728:138812. https://doi.org/10.1016/j.scitotenv.2020.138812 PMid:32335406 DOI: https://doi.org/10.1016/j.scitotenv.2020.138812

Shi D, Wu W, Wang Q, Xu K, Xie J, Wu J, et al. Clinical characteristics and factors associated with long-term viral excretion in patients with SARS-CoV-2 infection: A single center 28-day study. J Infect Dis. 2020;222(6):910-8. https://doi.org/10.1093/infdis/jiaa388 PMid:32614392 DOI: https://doi.org/10.1093/infdis/jiaa388

Zhang JJ, Dong X, Cao YY, Yuan YD, Yang YB, Yan YQ, et al. Clinical characteristics of 140 patients infected with SARS-CoV-2 in Wuhan, China. Allergy. 2020;75(7):1730-41. https://doi.org/10.1111/all.14238 PMid:32077115 DOI: https://doi.org/10.1111/all.14238

Shi Q, Zhang X, Jiang F, Zhang X, Hu N, Bimu C, et al. Clinical characteristics and risk factors for mortality of COVID- 19 patients with diabetes in Wuhan, China: A two-center, retrospective study. Diabetes Care. 2020;43(7):1382-91. https://doi.org/10.2337/dc20-0598 PMid:32409504 DOI: https://doi.org/10.2337/dc20-0598

Li X, Xu S, Yu M, Wang K, Tao Y, Zhou Y, et al. Risk factors for severity and mortality in adult COVID-19 inpatients in Wuhan. J Allergy Clin Immunol. 2020;146(1):110-8. https://doi.org/10.1016/j.jaci.2020.04.006 PMid:32294485 DOI: https://doi.org/10.1016/j.jaci.2020.04.006

Liu K, Chen Y, Lin R, Han K. Clinical features of COVID-19 in elderly patients: A comparison with young and middle-aged patients. J Infect. 2020;80(6):e14-8. https://doi.org/10.1016/j.jinf.2020.03.005 PMid:32171866 DOI: https://doi.org/10.1016/j.jinf.2020.03.005

Grubeck-Loebenstein B, Wick G. The aging of the immune system. Adv Immunol. 2002;80:243-84. https://doi.org/10.1016/s0065-2776(02)80017-7 PMid:12078483 DOI: https://doi.org/10.1016/S0065-2776(02)80017-7

Weksler ME. Changes in the B-cell repertoire with age. Vaccine. 2000;18(16):1624-8. https://doi.org/10.1016/ s0264-410x(99)00497-1 PMid:10689139 DOI: https://doi.org/10.1016/S0264-410X(99)00497-1

Chen T, Wu D, Chen H, Yan W, Yang D, Chen G, et al. Clinical characteristics of 113 deceased patients with coronavirus disease 2019: Retrospective study. BMJ. 2020;368:m1091. https://doi.org/10.1136/bmj.m1091 PMid:32217556 DOI: https://doi.org/10.1136/bmj.m1091

Zhang J, Wang X, Jia X, Li J, Hu K, Chen G, et al. Risk factors for disease severity, unimprovement, and mortality in COVID-19 patients in Wuhan, China. Clin Microbiol Infect. 2020;26(6):767-72. https://doi.org/10.1016/j.cmi.2020.04.012 PMid:32304745 DOI: https://doi.org/10.1016/j.cmi.2020.04.012

Terpos E, Ntanasis-Stathopoulos I, Elalamy I, Kastritis E, Sergentanis TN, Politou M, et al. Hematological findings and complications of COVID-19. Am J Hematol. 2020;95(7):834-47. https://doi.org/10.1002/ajh.25829 PMid:32282949 DOI: https://doi.org/10.1002/ajh.25829

Connors JM, Levy JH. COVID-19 and its implications for thrombosis and anticoagulation. Blood. 2020;135(23):2033-40. https://doi.org/10.1182/blood.2020006000 PMid:32339221 DOI: https://doi.org/10.1182/blood.2020006000

Iba T, Levy JH, Levi M, Thachil J. Coagulopathy in COVID- 19. J Thromb Haemost. 2020;1:14975. https://doi.org/10.1111/jth.14975 PMid:32558075 DOI: https://doi.org/10.1111/jth.14975

Di Micco P, Russo V, Carannante N, Imparato M, Rodolfi S, Cardillo G, et al. Clotting factors in COVID-19: Epidemiological association and prognostic values in different clinical presentations in an Italian cohort. J Clin Med. 2020;9(5):1371. https://doi.org/10.3390/jcm9051371 PMid:32392741 DOI: https://doi.org/10.3390/jcm9051371

Gao Y, Li T, Han M, Li X, Wu D, Xu Y, et al. Diagnostic utility of clinical laboratory data determinations for patients with the severe COVID-19. J Med Virol. 2020;92(7):791-6. https://doi.org/10.1002/jmv.25770 PMid:32181911 DOI: https://doi.org/10.1002/jmv.25770

Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020;395(10223):497-506. https://doi.org/10.1016/S0140-6736(20)30183-5 PMid:31986264 DOI: https://doi.org/10.1016/S0140-6736(20)30183-5

Li Y, Deng W, Xiong H, Li H, Chen Z, Nie Y, et al. Immune-related factors associated with pneumonia in 127 children with coronavirus disease 2019 in Wuhan. Pediatr Pulmonol. 2020;1:24907. https://doi.org/10.1002/ppul.24907 PMid:32543756 DOI: https://doi.org/10.1002/ppul.24907

Lu L, Zhong W, Bian Z, Li Z, Zhang K, Liang B, et al. A comparison of mortality-related risk factors of COVID-19, SARS, and MERS: A systematic review and meta-analysis. J Infect. 2020;81(4):e18-25. https://doi.org/10.1016/j.jinf.2020.07.002 PMid:32634459 DOI: https://doi.org/10.1016/j.jinf.2020.07.002

Li M, Dong Y, Wang H, Guo W, Zhou H, Zhang Z, et al. Cardiovascular disease potentially contributes to the progression and poor prognosis of COVID-19. Nutr Metab Cardiovasc Dis. 2020;30(7):1061-7. https://doi.org/10.1016/j.numecd.2020.04.013 PMid:32456948 DOI: https://doi.org/10.1016/j.numecd.2020.04.013

Li L, Zhang S, He B, Chen X, Zhao Q. Retrospective study of risk factors for myocardial damage in patients with critical coronavirus disease 2019 in Wuhan. J Am Heart Assoc. 2020;9(15):e016706. https://doi.org/10.1161/JAHA.120.016706 PMid:32600078 DOI: https://doi.org/10.1161/JAHA.120.016706

Kucuk A, Cure MC, Cure E. Can COVID-19 cause myalgia with a completely different mechanism? A hypothesis. Clin Rheumatol. 2020;39(7):2103-4. https://doi.org/10.1007/s10067-020-05178-1 PMid:32458242 DOI: https://doi.org/10.1007/s10067-020-05178-1

Downloads

Published

2020-11-07

How to Cite

1.
Jiang N, Liu Y, Yang B, Li Z, Si D, Ma P, Zhang J, Liu T, Yu Q. Analysis of the Factors Associated with Negative Conversion of Severe Acute Respiratory Syndrome Coronavirus 2 RNA of Coronavirus Disease 2019. Open Access Maced J Med Sci [Internet]. 2020 Nov. 7 [cited 2024 Nov. 21];8(T1):436-42. Available from: https://oamjms.eu/index.php/mjms/article/view/5488