Association of Overlapped and Un-overlapped Comorbidities with COVID-19 Severity and Treatment Outcomes: A Retrospective Cohort Study from Nine Provinces in China

Autor: Yan, Ma, Dong Shan, Zhu, Ren Bo, Chen, Nan Nan, Shi, Si Hong, Liu, Yi Pin, Fan, Gui Hui, Wu, Pu Ye, Yang, Jiang Feng, Bai, Hong, Chen, Li Ying, Chen, Qiao, Feng, Tuan Mao, Guo, Yong, Hou, Gui Fen, Hu, Xiao Mei, Hu, Yun Hong, Hu, Jin, Huang, Qiu Hua, Huang, Shao Zhen, Huang, Liang, Ji, Hai Hao, Jin, Xiao, Lei, Chun Yan, Li, Min Qing, Li, Qun Tang, Li, Xian Yong, Li, Hong De, Liu, Jin Ping, Liu, Zhang, Liu, Yu Ting, Ma, Ya, Mao, Liu Fen, Mo, Hui, Na, Jing Wei, Wang, Fang Li, Song, Sheng, Sun, Dong Ting, Wang, Ming Xuan, Wang, Xiao Yan, Wang, Yin Zhen, Wang, Yu Dong, Wang, Wei, Wu, Lan Ping, Wu, Yan Hua, Xiao, Hai Jun, Xie, Hong Ming, Xu, Shou Fang, Xu, Rui Xia, Xue, Chun, Yang, Kai Jun, Yang, Sheng Li, Yuan, Gong Qi, Zhang, Jin Bo, Zhang, Lin Song, Zhang, Shu Sen, Zhao, Wan Ying, Zhao, Kai, Zheng, Ying Chun, Zhou, Jun Teng, Zhu, Tian Qing, Zhu, Hua Min, Zhang, Yan Ping, Wang, Yong Yan, Wang
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Biomedical and Environmental Sciences
ISSN: 2214-0190
0895-3988
Popis: 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.
Databáze: OpenAIRE
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