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Plasma glucose levels and diabetes are independent predictors for mortality in patients with COVID-19

Published online by Cambridge University Press:  16 May 2022

Hui Long
Affiliation:
Tianyou Hospital, Wuhan University of Science and Technology, Wuhan, Hubei, P. R. China
Jiachen Li
Affiliation:
State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China
Rui Li
Affiliation:
Department of Healthcare, School of Health Sciences, Wuhan University, 115 Donghu Road, Wuhan, Hubei 430071, P. R. China Global Health Institute, Wuhan University, 8 South Donghu Road, Wuhan, Hubei 430072, P. R. China
Haiyang Zhang
Affiliation:
State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China Center for Disease Control and Prevention of Central Theater Command, Beijing, Shijingshan District, China
Honghan Ge
Affiliation:
State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China
Hui Zeng
Affiliation:
Tianyou Hospital, Wuhan University of Science and Technology, Wuhan, Hubei, P. R. China
Xi Chen
Affiliation:
Department of Thoracic and Vascular Surgery, Wuhan No. 1 Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, P. R. China
Qingbin Lu
Affiliation:
Department of Laboratorial Science and Technology, School of Public Health, Peking University, Beijing, P. R. China
Wanli Jiang
Affiliation:
Department of Thoracic Surgery, Renmin Hospital of Wuhan University, Wuhan 430060, P. R. China
Haolong Zeng
Affiliation:
Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, P. R. China
Tianle Che
Affiliation:
State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China
Xiaolei Ye
Affiliation:
State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China
Liqun Fang
Affiliation:
State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China
Ying Qin*
Affiliation:
Division of Infectious Disease, Key Laboratory of Surveillance and Early Warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, P. R. China
Qiang Wang*
Affiliation:
Institute of Infection, Immunology and Tumor Microenvironment, Hubei Province Key Laboratory of Occupational Hazard Identification and Control, Medical College, Wuhan University of Science and Technology, Wuhan 430065, P. R. China
Qingming Wu*
Affiliation:
Institute of Infection, Immunology and Tumor Microenvironment, Hubei Province Key Laboratory of Occupational Hazard Identification and Control, Medical College, Wuhan University of Science and Technology, Wuhan 430065, P. R. China
Hao Li*
Affiliation:
State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China
Wei Liu*
Affiliation:
State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China Department of Laboratorial Science and Technology, School of Public Health, Peking University, Beijing, P. R. China
*
Authors for correspondence: Ying Qin, E-mail: qinying@chinacdc.cn; Qiang Wang, E-mail: wangqiang@wust.edu.cn; Qingming Wu, E-mail: wuhe9224@sina.com; Wei Liu, E-mail: lwbime@163.com, liuwei@bmi.ac.cn; Hao Li, E-mail: lihao_1986@126.com
Authors for correspondence: Ying Qin, E-mail: qinying@chinacdc.cn; Qiang Wang, E-mail: wangqiang@wust.edu.cn; Qingming Wu, E-mail: wuhe9224@sina.com; Wei Liu, E-mail: lwbime@163.com, liuwei@bmi.ac.cn; Hao Li, E-mail: lihao_1986@126.com
Authors for correspondence: Ying Qin, E-mail: qinying@chinacdc.cn; Qiang Wang, E-mail: wangqiang@wust.edu.cn; Qingming Wu, E-mail: wuhe9224@sina.com; Wei Liu, E-mail: lwbime@163.com, liuwei@bmi.ac.cn; Hao Li, E-mail: lihao_1986@126.com
Authors for correspondence: Ying Qin, E-mail: qinying@chinacdc.cn; Qiang Wang, E-mail: wangqiang@wust.edu.cn; Qingming Wu, E-mail: wuhe9224@sina.com; Wei Liu, E-mail: lwbime@163.com, liuwei@bmi.ac.cn; Hao Li, E-mail: lihao_1986@126.com
Authors for correspondence: Ying Qin, E-mail: qinying@chinacdc.cn; Qiang Wang, E-mail: wangqiang@wust.edu.cn; Qingming Wu, E-mail: wuhe9224@sina.com; Wei Liu, E-mail: lwbime@163.com, liuwei@bmi.ac.cn; Hao Li, E-mail: lihao_1986@126.com
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Abstract

This study is performed to figure out how the presence of diabetes affects the infection, progression and prognosis of 2019 novel coronavirus disease (COVID-19), and the effective therapy that can treat the diabetes-complicated patients with COVID-19. A multicentre study was performed in four hospitals. COVID-19 patients with diabetes mellitus (DM) or hyperglycaemia were compared with those without these conditions and matched by propensity score matching for their clinical progress and outcome. Totally, 2444 confirmed COVID-19 patients were recruited, from whom 336 had DM. Compared to 1344 non-DM patients with age and sex matched, DM-COVID-19 patients had significantly higher rates of intensive care unit entrance (12.43% vs. 6.58%, P = 0.014), kidney failure (9.20% vs. 4.05%, P = 0.027) and mortality (25.00% vs. 18.15%, P < 0.001). Age and sex-stratified comparison revealed increased susceptibility to COVID-19 only from females with DM. For either non-DM or DM group, hyperglycaemia was associated with adverse outcomes, featured by higher rates of severe pneumonia and mortality, in comparison with non-hyperglycaemia. This was accompanied by significantly altered laboratory indicators including lymphocyte and neutrophil percentage, C-reactive protein and urea nitrogen level, all with correlation coefficients >0.35. Both diabetes and hyperglycaemia were independently associated with adverse prognosis of COVID-19, with hazard ratios of 10.41 and 3.58, respectively.

Information

Type
Original Paper
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press
Figure 0

Table 1. Comparison of demographic characteristics and clinical outcome between COVID-19 patients with or without DM

Figure 1

Table 2. Proportion of DM in the recruited COVID-19 patients vs. in the general population

Figure 2

Table 3. Clinical outcomes of COVID-19 patients with or without DM stratified by the glucose control status

Figure 3

Table 4. Association between demography and drug use with fatal outcomes in patients with COVID-19 by univariable and multivariable Cox regression analyses

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Long et al. supplementary material

Tables S1-S4

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