Journal of Shandong University (Health Sciences) ›› 2020, Vol. 58 ›› Issue (10): 60-65.doi: 10.6040/j.issn.1671-7554.0.2020.0690

Previous Articles     Next Articles

Risk factors of severe and critical patients with COVID-19 in Hubei, China

LIU Jun1*, LI Huan2*, ZHANG Shiyu2, ZHANG Peng3, AI Siqi2, TIAN Fei2, LIN Hualiang2   

  1. 1. Central Office, Qianjiang Center for Disease Control and Prevention, Qianjiang 433100, Hubei, China;
    2. Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, Guangdong, China;
    3. Institute of Preventive Medicine Information, Hubei Provincial Center for Disease Control and Prevention, Wuhan 430000, Hubei, China
  • Published:2020-10-08

PDF (PC)

172

Abstract: Objective To investigate the risk factors of severe and critical patients with coronavirus disease 2019(COVID-19)in Hubei, China. Methods All patients with COVID-19 registered in the National Legal Infectious Disease Reporting System of Hubei Provincial Center for Disease Control and Prevention, as of March 18, 2020, were recruited. According to the symptoms, the patients were divided into two groups: mild/moderate patients and severe/critical patients. Their general characteristics were described, and the risk factors of severe and critical patients with COVID-19 were explored by using a Logistic regression model. Results A total of 48 814 cases were included, of which 38 730 were mild/moderate patients and 10 084 were severe/critical patients. The median age was 54(41, 65)years. Multivariate analysis showed that the elderly, male, home workers, people in Wuhan City, migrants, longer interval between onset and diagnosis, low temperature, higher concentrations of PM2.5/PM10/SO2/O3 increased the risk of severe/critical diagnosis in patients with COVID-19. Conclusion The elderly, male, home workers, people in Wuhan City, migrants, longer interval between onset and diagnosis, low temperature, and air pollution exposure are risk factors for severe/critical COVID-19 patients. More attention should be paid to people with these characteristics.

Key words: Coronavirus disease 2019, Severe patients, Critical patients, Low temperature, Air pollution

CLC Number: 

  • R184
[1] Arentz M, Yim E, Klaff L, et al. Characteristics and outcomes of 21 critically Ill patients with COVID-19 in Washington State[J]. JAMA, 2020, 323(16): 1612-1614.
[2] Yang X, Yu Y, Xu J, et al. Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study[J]. Lancet Respir Med, 2020, 8(5): 475-481.
[3] Bhatraju PK, Ghassemieh BJ, Nichols M, et al. Covid-19 in critically Ill patients in the seattle region-case series[J]. N Engl J Med, 2020, 382(21): 2012-2022.
[4] Menendez JA. Metformin and SARS-CoV-2: mechanistic lessons on air pollution to weather the cytokine/thrombotic storm in COVID-19[J]. Aging(Albany NY), 2020, 12(10): 8760-8765.
[5] Zhu YJ, Xie JG, Huang FM, et al. Association between short-term exposure to air pollution and COVID-19 infection: evidence from China[J]. Sci Total Environ, 2020, 727: 138704. doi: 10.1016/j.scitotenv.2020.138704.
[6] van Doremalen N, Bushmaker T, Munster VJ. Stability of Middle East respiratory syndrome coronavirus(MERS-CoV)under different environmental conditions[J]. Euro Surveill, 2013, 18(38): 20590. doi: 10.2807/1560-7917.es2013.18.38.20590.
[7] Chan KH, Peiris JS, Lam SY, et al. The effects of temperature and relative humidity on the viability of the SARS coronavirus[J]. Adv Virol, 2011, 2011: 734690. doi: 10.1155/2011/734690.
[8] Cai J, Meng X, Wang C, et al. The cold effects on circulatory inflammation, thrombosis and vasoconstriction in type 2 diabetic patients[J]. Sci Total Environ, 2016, 568: 271-277. doi: 10.1016/j.scitotenv.2016.06.030.
[9] Conticini E, Frediani B, Caro D. Can atmospheric pollution be considered a co-factor in extremely high level of SARS-CoV-2 lethality in Northern Italy?[J]. Environ Pollut, 2020, 261: 114465. doi: 10.1016/j.envpol.2020.114465.
[10] 中华人民共和国国家卫生健康委员会. 关于印发新型冠状病毒肺炎诊疗方案(试行第七版)的通知[EB/OL].(2020-04-21)[2020-04-21]. http://www.nhc.gov.cn/xcs/zhengcwj/202003/46c9294a7dfe4cef80dc7f5912eb1989.shtml.
[11] Lin HL, Liu T, Xiao JP, et al. Mortality burden of ambient fine particulate air pollution in six Chinese cities: results from the Pearl River Delta study[J]. Environ Int, 2016, 96: 91-97. doi: 10.1016/j.envint.2016.09.007.
[12] 楼淑萍, 刘攀越, 陈辉. 新型冠状病毒肺炎患者发生重症、危重症危险因素的Meta分析[J].第三军医大学学报, 2020, 42(14): 1469-1475. LOU Shuping, LIU Panyue, CHEN Hui. Risk factors of severe and critical coronavirus disease 2019: a meat-analysis[J]. Acta Academiae Medicinae Militaris Tertiae, 2020,42(14):1469-1475.
[13] Lowen AC, Mubareka S, Steel J, et al. Influenza virus transmission is dependent on relative humidity and temperature[J]. PLoS Pathog, 2007, 3(10): 1470-1476.
[14] Peykari N, Djalalinia S, Qorbani M, et al. Socioeconomic inequalities and diabetes: a systematic review from Iran[J]. J Diabetes Metab Disord, 2015, 14: 8. doi: 10.1186/s40200-015-0135-4.?eCollection 2015.
[15] Kolahi AA, Moghisi A, Soleiman Ekhtiari Y. Socio-demographic determinants of obesity indexes in Iran: findings from a nationwide STEPS survey[J]. Health Promot Perspect, 2018, 8(3):187-194.
[16] 周粟,袁敏,宋凤祥, 等.上海地区重型及危重型新型冠状病毒肺炎临床特点与胸部计算机断层扫描表现[J].第二军医大学学报, 2020, 41(6): 581-587. ZHOU Su, YUAN Min, SONG Fengxiang, et al. Clinical characteristics and chest computed tomography findings of severe and critical coronavirus disease 2019 in Shanghai, China[J]. Acad J Sec Mil Med Univ, 2020, 41(6): 581-587.
[17] 孙煜,方鹏骞.新冠肺炎疫情下我国农村基层卫生防控能力建设分析[J].中国卫生事业管理, 2020, 37(5): 329-331. SUN Yu, FANG Pengqian. Analyzing the capacity construction of prevention and control of Chinese rural primary healthcare in the outbreak of COVID-19[J]. Chinese Health Service Management, 2020, 37(5): 329-331.
[18] Zhang Z, Yao W, Wang Y, et al. Wuhan and Hubei COVID-19 mortality analysis reveals the critical role of timely supply of medical resources[J]. J Infect, 2020, 81(1): 147-178.
[19] Ma YL, Zhao YD, Liu JT, et al. Effects of temperature variation and humidity on the death of COVID-19 in Wuhan, China[J]. Sci Total Environ, 2020, 724: 138226. doi: 10.1016/j.scitotenv.2020.138226.
[20] Pope CA, 3rd, Bhatnagar A, McCracken JP, et al. Exposure to fine particulate air pollution is associated with endothelial injury and systemic inflammation[J]. Circ Res, 2016, 119(11): 1204-1214.
[21] Cao Y, Chen M, Dong D, et al. Environmental pollutants damage airway epithelial cell cilia: implications for the prevention of obstructive lung diseases[J]. Thorac Cancer, 2020, 11(3): 505-510.
[22] 刁琴琴, 凌艺辉, 李美珍, 等. 大气PM(10)暴露对居民血浆炎症及肺损伤标志物的影响[J]. 环境与健康杂志, 2019, 36(2): 103-106. DIAO Qinqin, LING Yihui, LI Meizhen, et al. Association between ambient inhalable particulate matter short-term exposure and inflammation and lung injury-related biomarkers[J]. J Environ Health, 2019, 36(2): 103-106.
[23] Kan H, Chen BH, Fu C, et al. Relationship between ambient air pollution and daily mortality of SARS in Beijing[J]. Biomedical and Environmental Sciences, 2005, 18(1): 1-4.
[24] Cui Y, Zhang ZF, Froines J, et al. Air pollution and case fatality of SARS in the Peoples Republic of China: an ecologic study[J]. Environmental Health, 2003, 2(1): 15. doi: 10.1186/1476-069X-2-15.
[1] WANG Bin, BU Xuehui, KONG Xianggen, ZHANG Zhaohua, WU Anzhao, XIAO Di, JIANG Xuemei. Comparison of the clinical characteristics between 37 adults and 10 children with COVID-19 [J]. Journal of Shandong University (Health Sciences), 2020, 58(10): 112-116.
[2] WANG Ling, CAO Haixia, ZHANG Ling, ZHANG Wenna, PAN Yanping, SHI Ying, ZHANG Wei, CUI Feng. Investigation and analysis of the characteristics of a family cluster of coronavirus disease 2019 in Zibo [J]. Journal of Shandong University (Health Sciences), 2020, 58(10): 100-104.
[3] BAI Yao, CHEN Zhijun, SONG Shuxuan, HE Zhen, CHEN Baozhong, SHAO Zhongjun, LIU Kun. Investigation of a family cluster outbreak of coronavirus disease 2019 in Xian [J]. Journal of Shandong University (Health Sciences), 2020, 58(10): 95-99.
[4] ZHANG Hui, SONG Shuxuan, LIU Jifeng, HE Zhen, SHAO Zhongjun, LIU Kun. Epidemiological characteristics of COVID-19 in Xi’an city [J]. Journal of Shandong University (Health Sciences), 2020, 58(10): 89-94.
[5] LIU Lili, JIA Yan, QI Chang, ZHU Yuchen, LI Chunyu, SHE Kaili, LIU Tingxuan, LI Xiujun. Clustering distribution of COVID-19 in Wenzhou from January to March 2020 based on spatiotemporal analysis [J]. Journal of Shandong University (Health Sciences), 2020, 58(10): 82-88.
[6] LIU Tingxuan, QI Chang, SHE Kaili, JIA Yan, ZHU Yuchen, LI Chunyu, LIU Lili, WANG Xu, ZHANG Zhihua, LI Xiujun. Epidemiological characteristics and spatial-temporal clustering of COVID-19 in Hebei Province [J]. Journal of Shandong University (Health Sciences), 2020, 58(10): 74-81.
[7] JIA Yan, LI Chunyu, LIU Lili, SHE Kaili, LIU Tingxuan, ZHU Yuchen, QI Chang, ZHANG Dandan, WANG Xu, CHEN Enfu, LI Xiujun. Epidemic characteristics and spatial analysis of COVID-19 in Zhejiang Province [J]. Journal of Shandong University (Health Sciences), 2020, 58(10): 66-73.
[8] QI Chang, ZHU Yuchen, LI Chunyu, LIU Lili, ZHANG Dandan, WANG Xu, SHE Kaili, CHEN Ming, KANG Dianmin, LI Xiujun. Influence factors of COVID-19 in Shandong Province based on geographically weighted generalized linear model [J]. Journal of Shandong University (Health Sciences), 2020, 58(10): 53-59.
[9] SHE Kaili, ZHANG Dandan, QI Chang, LIU Tingxuan, JIA Yan, ZHU Yuchen, LI Chunyu, LIU Lili, WANG Xu, SU Hong, LI Xiujun. Epidemiological characteristics and incubation period of coronavirus disease 2019 in Anhui Province [J]. Journal of Shandong University (Health Sciences), 2020, 58(10): 44-52.
[10] LI Chunyu, ZHU Yuchen, QI Chang, LIU Lili, ZHANG Dandan, WANG Xu, XU Xueli, LI Xiujun. Epidemic dynamics of COVID-19 in Xinyang City, Henan Province [J]. Journal of Shandong University (Health Sciences), 2020, 58(10): 38-43.
[11] JIN Xinye, LU Zhenzhen, DING Zhongxing, CHEN Feng, PENG Zhihang. A dynamic modeling study on the effects of Wuhan traffic control and centralized quarantine measures on COVID-19 epidemic [J]. Journal of Shandong University (Health Sciences), 2020, 58(10): 25-31.
[12] XU Lijun, LIU Wenhui, LIU Yuan, LI Meixia, LUO Lei, OU Chunquan. Construction of SEIQCR epidemic model and its application in the evaluation of public health interventions on COVID-19 in Guangzhou [J]. Journal of Shandong University (Health Sciences), 2020, 58(10): 20-24.
[13] LI Xiujun, LI Xinlou, LIU Kun, ZHAO Xiaobo, MA Meng, SUN Bo. Application of geographic information system in the control of COVID-19 epidemic [J]. Journal of Shandong University (Health Sciences), 2020, 58(10): 13-19.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
Copyright 2018 © Editorial office of Journal of Shandong University (Health Sciences)
Supported by Beijing Magtech Co.Ltd