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Association of Overlapped and Un-overlapped Comorbidities with COVID-19 Severity and Treatment Outcomes: A Retrospective Cohort Study from Nine Provinces in China.
Ma, Yan; Zhu, Dong Shan; Chen, Ren Bo; Shi, Nan Nan; Liu, Si Hong; Fan, Yi Pin; Wu, Gui Hui; Yang, Pu Ye; Bai, Jiang Feng; Chen, Hong; Chen, Li Ying; Feng, Qiao; Guo, Tuan Mao; Hou, Yong; Hu, Gui Fen; Hu, Xiao Mei; Hu, Yun Hong; Huang, Jin; Huang, Qiu Hua; Huang, Shao Zhen; Ji, Liang; Jin, Hai Hao; Lei, Xiao; Li, Chun Yan; Li, Min Qing; Li, Qun Tang; Li, Xian Yong; Liu, Hong De; Liu, Jin Ping; Liu, Zhang; Ma, Yu Ting; Mao, Ya; Mo, Liu Fen; Na, Hui; Wang, Jing Wei; Song, Fang Li; Sun, Sheng; Wang, Dong Ting; Wang, Ming Xuan; Wang, Xiao Yan; Wang, Yin Zhen; Wang, Yu Dong; Wu, Wei; Wu, Lan Ping; Xiao, Yan Hua; Xie, Hai Jun; Xu, Hong Ming; Xu, Shou Fang; Xue, Rui Xia; Yang, Chun.
  • Ma Y; Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing 100700, China.
  • Zhu DS; Centre for Health Management and Policy Research, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong, China.
  • Chen RB; Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing 100700, China.
  • Shi NN; Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing 100700, China.
  • Liu SH; Institute of Information on Traditional Chinese Medicine, China Academy of Chinese Medical Sciences, Beijing 100700, China.
  • Fan YP; Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing 100700, China.
  • Wu GH; Department of Tuberculosis, The Public Health Clinical Center of Chengdu, Chengdu 610066, Sichuan, China.
  • Yang PY; Department of Infectious Disease, Shaanxi Infectious Disease Hospital, Xi'an 610113, Shaanxi, China.
  • Bai JF; Department of Infectious Disease, Yulin Chinese Medicine Hospital, Yulin 719000, Shaanxi, China.
  • Chen H; President's Office, The First Hospital of Qiqihar, Qiqihar 161005, Heilongjiang, China.
  • Chen LY; Department of Traditional Chinese Medicine, Shangluo Central Hospital, Shangluo 726000, Shaanxi, China.
  • Feng Q; Department of Traditional Chinese Medicine, The People's Hospital of Qitaihe, Qitaihe 154603, Heilongjiang, China.
  • Guo TM; Department of Scientific Research, Xianyang Central Hospital, Xianyang 712000, Shaanxi, China.
  • Hou Y; Department of traditional Chinese medicine, The First Affiliated Hospital of Anhui University of Traditional Chinese Medicine, Hefei 230012, Anhui, China.
  • Hu GF; Department of Infectious Disease, Heping Hospital Affiliated to Changzhi Medical College, Changzhi 046000, Shanxi, China.
  • Hu XM; Department of Traditional Chinese Medicine, Langfang Hospital of Chinese Medicine, Langfang 065000, Heibei, China.
  • Hu YH; Department of Traditional Chinese Medicine, Xingtai Hospital of Chinese Medicine, Xingtai 054001, Heibei, China.
  • Huang J; Department of Traditional Chinese Medicine, The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning 168600, Guangxi, China.
  • Huang QH; Department of Traditional Chinese Medicine, The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning 168600, Guangxi, China.
  • Huang SZ; Department of Traditional Chinese Medicine, The First People's Hospital of Fangchenggang, Fangchenggang 538001, Guangxi, China.
  • Ji L; Department of Traditional Chinese Medicine, Mianyang Hospital of Traditional Chinese Medicine, Mianyang 621000, Sichuan, China.
  • Jin HH; Department of Traditional Chinese Medicine, Liuzhou People's Hospital, Liuzhou 545006, Gansu, China.
  • Lei X; Department of Traditional Chinese Medicine, Affiliated Hospital of North Sichuan Medical College, Nanyun 637000, Sichuan, China.
  • Li CY; Department of Infectious Disease, Yan'an Second People's Hospital, Yan'an 716000, Shaanxi, China.
  • Li MQ; Department of Traditional Chinese Medicine, Dazhou Central Hospital, Dazhou 635000, Sichuan, China.
  • Li QT; Chongqing Traditional Chinese Medicine Hospital, Chongqing 400011, China.
  • Li XY; The Second People's Hospital of Neijiang, Neijiang 641000, Sichuan, China.
  • Liu H; Shijiazhuang Fifth Hospital, Shijiazhuang 050021, Hebei, China.
  • Liu JP; Department of Infectious Disease, The Fourth People's Hospital of Taiyuan, Taiyuan 030053, Shanxi, China.
  • Liu Z; Department of Traditional Chinese Medicine, The First Hospital of Suihua City, Suihua 152053, Heilongjiang, China.
  • Ma YT; Department of Traditional Chinese Medicine, The Fourth People's Hospital of Nanning, Nanning 530023, Guangxi, China.
  • Mao Y; Department of Infectious Disease, Ankang Hospital of Traditional Chinese Medicine, Ankang 725000, Shaanxi, China.
  • Mo LF; Department of Infectious Disease, Beihai Hospital of Chinese Medicine, Beihai 536000, Guangxi, China.
  • Na H; Department of Infectious Disease, Harbin Infectious Disease Hospital, Harbin 150036, Heilongjiang, China.
  • Wang JW; Department of Infectious Disease, Harbin Infectious Disease Hospital, Harbin 150036, Heilongjiang, China.
  • Song FL; Department of Infectious Disease, The Third People's Hospital of Linfen, Linfen 041000, Shanxi, China.
  • Sun S; Department of Traditional Chinese Medicine, Chengde Hospital of Traditional Chinese Medicine, Chengde 067000, Hehei, China.
  • Wang DT; Department of Infectious Disease, Datong Fourth Hospital, Datong 037008, Shanxi, China.
  • Wang MX; Department of Traditional Chinese Medicine, Suining Central Hospital, Suining 629000, Sichuan, China.
  • Wang XY; Department of Infectious Disease, Jinzhong Infectious Disease Hospital, Jinzhong 030600, Shanxi, China.
  • Wang YZ; Department of Infectious Disease, Jincheng People's Hospital, Jincheng 048026, Shanxi, China.
  • Wang YD; Hengshui Hospital of Chinese Medicine, Hengshui 053000, Heibei, China.
  • Wu W; President's office, Hanzhong Central Hospital, Hanzhong 723000, Hubei, China.
  • Wu LP; Department of Infectious Disease, Shuozhou People's Hospital, Shuozhou 036002, Shanxi, China.
  • Xiao YH; Department of Traditional Chinese Medicine, Mudanjiang Kangan Hospital, Mudanjiang 157011, Heilongjiang, China.
  • Xie HJ; Department of Infectious Disease, Xinzhou People's Hospital, Xinzhou 034000, Shanxi, China.
  • Xu HM; Department of Infectious Disease, Daqing Second Hospital, Daqing 163000, Heilongjiang, China.
  • Xu SF; Department of Traditional Chinese Medicine,Jiamusi Infectious Disease Hospital, Jiamusi 154007, Heilongjiang, China.
  • Xue RX; Department of Infectious Disease, Yuncheng Second Hospital, Yuncheng 044000, Shanxi, China.
  • Yang C; Department of Traditional Chinese Medicine, Hanzhong Hospital for Infectious Diseases, Hanzhong 723000, Hubei, China.
Biomed Environ Sci ; 33(12): 893-905, 2020 Dec 20.
Article in English | MEDLINE | ID: covidwho-1060079
Semantic information from SemMedBD (by NLM)
1. COVID-19 PROCESS_OF Patients
Subject
COVID-19
Predicate
PROCESS_OF
Object
Patients
2. Comorbidity PROCESS_OF Patients
Subject
Comorbidity
Predicate
PROCESS_OF
Object
Patients
3. Comorbidity PREDISPOSES COVID-19
Subject
Comorbidity
Predicate
PREDISPOSES
Object
COVID-19
4. Electrolyte imbalance ASSOCIATED_WITH GJA1 gene|GJA1
Subject
Electrolyte imbalance
Predicate
ASSOCIATED_WITH
Object
GJA1 gene|GJA1
5. Comorbidity PROCESS_OF Male population group
Subject
Comorbidity
Predicate
PROCESS_OF
Object
Male population group
6. Severe disease PROCESS_OF Woman
Subject
Severe disease
Predicate
PROCESS_OF
Object
Woman
7. Comorbidity PROCESS_OF Woman
Subject
Comorbidity
Predicate
PROCESS_OF
Object
Woman
8. Cardiovascular Diseases PREDISPOSES COVID-19
Subject
Cardiovascular Diseases
Predicate
PREDISPOSES
Object
COVID-19
9. Diabetes PREDISPOSES COVID-19
Subject
Diabetes
Predicate
PREDISPOSES
Object
COVID-19
10. Hyperlipidemia PREDISPOSES COVID-19
Subject
Hyperlipidemia
Predicate
PREDISPOSES
Object
COVID-19
11. Hypertensive disease PREDISPOSES COVID-19
Subject
Hypertensive disease
Predicate
PREDISPOSES
Object
COVID-19
12. Lung diseases PREDISPOSES COVID-19
Subject
Lung diseases
Predicate
PREDISPOSES
Object
COVID-19
13. Electrolyte imbalance PREDISPOSES COVID-19
Subject
Electrolyte imbalance
Predicate
PREDISPOSES
Object
COVID-19
14. Fatty Liver Disease PREDISPOSES COVID-19
Subject
Fatty Liver Disease
Predicate
PREDISPOSES
Object
COVID-19
15. COVID-19 PROCESS_OF Patients
Subject
COVID-19
Predicate
PROCESS_OF
Object
Patients
16. Comorbidity PROCESS_OF Patients
Subject
Comorbidity
Predicate
PROCESS_OF
Object
Patients
17. Comorbidity PREDISPOSES COVID-19
Subject
Comorbidity
Predicate
PREDISPOSES
Object
COVID-19
18. Electrolyte imbalance ASSOCIATED_WITH GJA1 gene|GJA1
Subject
Electrolyte imbalance
Predicate
ASSOCIATED_WITH
Object
GJA1 gene|GJA1
19. Comorbidity PROCESS_OF Male population group
Subject
Comorbidity
Predicate
PROCESS_OF
Object
Male population group
20. Severe disease PROCESS_OF Woman
Subject
Severe disease
Predicate
PROCESS_OF
Object
Woman
21. Comorbidity PROCESS_OF Woman
Subject
Comorbidity
Predicate
PROCESS_OF
Object
Woman
22. Cardiovascular Diseases PREDISPOSES COVID-19
Subject
Cardiovascular Diseases
Predicate
PREDISPOSES
Object
COVID-19
23. Diabetes PREDISPOSES COVID-19
Subject
Diabetes
Predicate
PREDISPOSES
Object
COVID-19
24. Hyperlipidemia PREDISPOSES COVID-19
Subject
Hyperlipidemia
Predicate
PREDISPOSES
Object
COVID-19
25. Hypertensive disease PREDISPOSES COVID-19
Subject
Hypertensive disease
Predicate
PREDISPOSES
Object
COVID-19
26. Lung diseases PREDISPOSES COVID-19
Subject
Lung diseases
Predicate
PREDISPOSES
Object
COVID-19
27. Electrolyte imbalance PREDISPOSES COVID-19
Subject
Electrolyte imbalance
Predicate
PREDISPOSES
Object
COVID-19
28. Fatty Liver Disease PREDISPOSES COVID-19
Subject
Fatty Liver Disease
Predicate
PREDISPOSES
Object
COVID-19
ABSTRACT

OBJECTIVE:

Several COVID-19 patients have overlapping comorbidities. The independent role of each component contributing to the risk of COVID-19 is unknown, and how some non-cardiometabolic comorbidities affect the risk of COVID-19 remains unclear.

METHODS:

A retrospective follow-up design was adopted. A total of 1,160 laboratory-confirmed patients were enrolled from nine provinces in China. Data on comorbidities were obtained from the patients' medical records. Multivariable logistic regression models were used to estimate the odds ratio ( OR) and 95% confidence interval (95% CI) of the associations between comorbidities (cardiometabolic or non-cardiometabolic diseases), clinical severity, and treatment outcomes of COVID-19.

RESULTS:

Overall, 158 (13.6%) patients were diagnosed with severe illness and 32 (2.7%) had unfavorable outcomes. Hypertension (2.87, 1.30-6.32), type 2 diabetes (T2DM) (3.57, 2.32-5.49), cardiovascular disease (CVD) (3.78, 1.81-7.89), fatty liver disease (7.53, 1.96-28.96), hyperlipidemia (2.15, 1.26-3.67), other lung diseases (6.00, 3.01-11.96), and electrolyte imbalance (10.40, 3.00-26.10) were independently linked to increased odds of being severely ill. T2DM (6.07, 2.89-12.75), CVD (8.47, 6.03-11.89), and electrolyte imbalance (19.44, 11.47-32.96) were also strong predictors of unfavorable outcomes. Women with comorbidities were more likely to have severe disease on admission (5.46, 3.25-9.19), while men with comorbidities were more likely to have unfavorable treatment outcomes (6.58, 1.46-29.64) within two weeks.

CONCLUSION:

Besides hypertension, diabetes, and CVD, fatty liver disease, hyperlipidemia, other lung diseases, and electrolyte imbalance were independent risk factors for COVID-19 severity and poor treatment outcome. Women with comorbidities were more likely to have severe disease, while men with comorbidities were more likely to have unfavorable treatment outcomes.
Subject(s)
Keywords

Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Cohort study / Observational study / Prognostic study Topics: Long Covid Limits: Adult / Aged / Female / Humans / Male / Middle aged Country/Region as subject: Asia Language: English Journal: Biomed Environ Sci Journal subject: Environmental Health Year: 2020 Document Type: Article Affiliation country: Bes2020.123

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Cohort study / Observational study / Prognostic study Topics: Long Covid Limits: Adult / Aged / Female / Humans / Male / Middle aged Country/Region as subject: Asia Language: English Journal: Biomed Environ Sci Journal subject: Environmental Health Year: 2020 Document Type: Article Affiliation country: Bes2020.123