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1000 Titel
  • Comorbidity and its impact on 1590 patients with Covid-19 in China: A Nationwide Analysis
1000 Autor/in
  1. Guan, Wei-Jie |
  2. Liang, Wen-Hua |
  3. Zhao, Yi |
  4. Liang, Heng-Rui |
  5. Chen, Zi-Sheng |
  6. Li, Yi-Min |
  7. Liu, Xiao-Qing |
  8. Chen, Ru-Chong |
  9. Tang, Chun-Li |
  10. Wang, Tao |
  11. Ou, Chun-Quan |
  12. Li, Li |
  13. Chen, Ping-Yan |
  14. Sang, Ling |
  15. Wang, Wei |
  16. Li, Jian-Fu |
  17. Li, Cai-Chen |
  18. Ou, Li-Min |
  19. Cheng, Bo |
  20. Xiong, Shan |
  21. Ni, Zheng-Yi |
  22. Xiang, Jie |
  23. Hu, Yu |
  24. Liu, Lei |
  25. Shan, Hong |
  26. Lei, Chun-Liang |
  27. Peng, Yi-Xiang |
  28. Wei, Li |
  29. Liu, Yong |
  30. Hu, Ya-Hua |
  31. Peng, Peng |
  32. Wang, Jian-Ming |
  33. Liu, Ji-Yang |
  34. Chen, Zhong |
  35. Li, Gang |
  36. Zheng, Zhi-Jian |
  37. Qiu, Shao-Qin |
  38. Luo, Jie |
  39. Ye, Chang-Jiang |
  40. Zhu, Shao-Yong |
  41. Cheng, Lin-Ling |
  42. Ye, Feng |
  43. Li, Shi-Yue |
  44. Zheng, Jin-Ping |
  45. Zhang, Nuo-Fu |
  46. Zhong, Nan-Shan |
  47. He, Jian-Xing |
1000 Erscheinungsjahr 2020
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2020-03-26
1000 Erschienen in
1000 Quellenangabe
  • Early view
1000 Copyrightjahr
  • 2020
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1183/13993003.00547-2020 |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7098485/ |
1000 Ergänzendes Material
  • https://erj.ersjournals.com/content/early/2020/03/17/13993003.00547-2020.figures-only |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • BACKGROUND: The coronavirus disease 2019 (Covid-19) outbreak is evolving rapidly worldwide. OBJECTIVE: To evaluate the risk of serious adverse outcomes in patients with coronavirus disease 2019 (Covid-19) by stratifying the comorbidity status. METHODS: We analysed the data from 1590 laboratory-confirmed hospitalised patients 575 hospitals in 31 province/autonomous regions/provincial municipalities across mainland China between December 11(th), 2019 and January 31(st), 2020. We analyse the composite endpoints, which consisted of admission to intensive care unit, or invasive ventilation, or death. The risk of reaching to the composite endpoints was compared according to the presence and number of comorbidities. RESULTS: The mean age was 48.9 years. 686 patients (42.7%) were females. Severe cases accounted for 16.0% of the study population. 131 (8.2%) patients reached to the composite endpoints. 399 (25.1%) reported having at least one comorbidity. The most prevalent comorbidity was hypertension (16.9%), followed by diabetes (8.2%). 130 (8.2%) patients reported having two or more comorbidities. After adjusting for age and smoking status, COPD [hazards ratio (HR) 2.681, 95% confidence interval (95%CI) 1.424-5.048], diabetes (HR 1.59, 95%CI 1.03-2.45), hypertension (HR 1.58, 95%CI 1.07-2.32) and malignancy (HR 3.50, 95%CI 1.60-7.64) were risk factors of reaching to the composite endpoints. The HR was 1.79 (95%CI 1.16-2.77) among patients with at least one comorbidity and 2.59 (95%CI 1.61-4.17) among patients with two or more comorbidities. CONCLUSION: Among laboratory-confirmed cases of Covid-19, patients with any comorbidity yielded poorer clinical outcomes than those without. A greater number of comorbidities also correlated with poorer clinical outcomes.
1000 Sacherschließung
gnd 1206347392 COVID-19
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
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1000 Label
1000 Förderer
  1. National Health and Family Planning Commission of the People's Republic of China |
  2. Guangdong Science and Technology Department |
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  2. -
1000 Förderprogramm
  1. -
  2. -
1000 Dateien
1000 Förderung
  1. 1000 joinedFunding-child
    1000 Förderer National Health and Family Planning Commission of the People's Republic of China |
    1000 Förderprogramm -
    1000 Fördernummer -
  2. 1000 joinedFunding-child
    1000 Förderer Guangdong Science and Technology Department |
    1000 Förderprogramm -
    1000 Fördernummer -
1000 Objektart article
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1000 @id frl:6419652.rdf
1000 Erstellt am 2020-04-02T08:13:49.379+0200
1000 Erstellt von 122
1000 beschreibt frl:6419652
1000 Bearbeitet von 122
1000 Zuletzt bearbeitet Thu Apr 02 08:15:37 CEST 2020
1000 Objekt bearb. Thu Apr 02 08:15:17 CEST 2020
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