Yili Zhang1, Juan Wang1, Nannan Tan1, KangJia Du1, Kuo Gao1, Jiacheng Zuo1, Xiaoguang Lu1, Yan Ma2, Yong Hou3, Quntang Li4, Hongming Xu5, Jin Huang6, Qiuhua Huang6, Hui Na7, Jingwei Wang7, Xiaoyan Wang8, Yanhua Xiao9, Junteng Zhu10, Hong Chen11, Zhang Liu12, Mingxuan Wang13, Linsong Zhang14, Shuzhen Guo1, Wei Wang1. 1. Beijing University of Chinese Medicine, Beijing, China. 2. Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China. 3. The First Affiliated Hospital of Anhui University of Traditional Chinese Medicine, Hefei, Anhui, China. 4. Chongqing Traditional Chinese Medicine Hospital, Chongqing, China. 5. Department of Infectious Disease, Daqing Second Hospital, Daqing, Heilongjiang, China. 6. Department of Traditional Chinese Medicine, The People's Hospital of GuangXi Zhuang Autonomous Region, Nanning, Guangxi, China. 7. Department of Infectious Disease, Harbin Infectious Disease Hospital, Harbin, Heilongjiang, China. 8. Department of Infectious Disease, Jinzhong Infectious Disease Hospital, Jinzhong, Shanxi, China. 9. Department of Traditional Chinese Medicine, Mudanjiang Kangan Hospital, Mudanjiang, Heilongjiang, China. 10. Department of Rehabilitation Medicine, The Affiliated Hospital of Putian College, Putian, Fujian, China. 11. President's Office, The First Hospital of Qiqihar, Qiqihar, Heilongjiang, China. 12. Department of Traditional Chinese Medicine, The First Hospital of Suihua City, Suihua, Heilongjiang, China. 13. Department of Traditional Chinese Medicine, Suining Central Hospital, Suining, Sichuan, China. 14. Department of Traditional Chinese Medicine, Hospital (T·C·M) Affiliated to Southwest Medical University, Luzhou, Sichuan, China.
Abstract
METHODS: In this multicenter retrospective study, patients with COVID-19 in China were included and classified into two groups according to whether they were complicated with diabetes or not. Demographic symptoms and laboratory data were extracted from medical records. Univariable and multivariable logistic regression methods were used to explore the risk factors. RESULTS: 538 COVID-19 patients were finally included in this study, of whom 492 were nondiabetes and 46 were diabetes. The median age was 47 years (IQR 35.0-56.0). And the elderly patients with diabetes were more likely to have dry cough, and the alanine aminotransferase, lactate dehydrogenase, Ca, and mean hemoglobin recovery rate were higher than the other groups. Furthermore, we also found the liver and kidney function of male patients was worse than that of female patients, while female cases should be paid more attention to the occurrence of bleeding and electrolyte disorders. Moreover, advance age, blood glucose, gender, prothrombin time, and total cholesterol could be considered as risk factors for COVID-19 patients with diabetes through the multivariable logistic regression model in our study. CONCLUSION: The potential risk factors found in our study showed a major piece of the complex puzzle linking diabetes and COVID-19 infection. Meanwhile, focusing on gender and age factors in COVID-19 patients with or without diabetes, specific clinical characteristics, and risk factors should be paid more attention by clinicians to figure out a targeted intervention to improve clinical efficacy worldwide.
METHODS: In this multicenter retrospective study, patients with COVID-19 in China were included and classified into two groups according to whether they were complicated with diabetes or not. Demographic symptoms and laboratory data were extracted from medical records. Univariable and multivariable logistic regression methods were used to explore the risk factors. RESULTS: 538 COVID-19 patients were finally included in this study, of whom 492 were nondiabetes and 46 were diabetes. The median age was 47 years (IQR 35.0-56.0). And the elderly patients with diabetes were more likely to have dry cough, and the alanine aminotransferase, lactate dehydrogenase, Ca, and mean hemoglobin recovery rate were higher than the other groups. Furthermore, we also found the liver and kidney function of male patients was worse than that of female patients, while female cases should be paid more attention to the occurrence of bleeding and electrolyte disorders. Moreover, advance age, blood glucose, gender, prothrombin time, and total cholesterol could be considered as risk factors for COVID-19 patients with diabetes through the multivariable logistic regression model in our study. CONCLUSION: The potential risk factors found in our study showed a major piece of the complex puzzle linking diabetes and COVID-19 infection. Meanwhile, focusing on gender and age factors in COVID-19 patients with or without diabetes, specific clinical characteristics, and risk factors should be paid more attention by clinicians to figure out a targeted intervention to improve clinical efficacy worldwide.
Authors: A Bukowska; L Spiller; C Wolke; U Lendeckel; S Weinert; J Hoffmann; P Bornfleth; I Kutschka; A Gardemann; B Isermann; A Goette Journal: Exp Biol Med (Maywood) Date: 2017-06-29
Authors: Alexander V Sorokin; Sotirios K Karathanasis; Zhi-Hong Yang; Lita Freeman; Kazuhiko Kotani; Alan T Remaley Journal: FASEB J Date: 2020-06-26 Impact factor: 5.191