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Clinical characteristics of novel coronavirus cases in tertiary hospitals in Hubei Province
Open accessAbstract
Background: The 2019 novel coronavirus (2019-nCoV) causing an outbreak of pneumonia in Wuhan, Hubei province of China was isolated in January 2020. This study aims to investigate its epidemiologic history, and analyze the clinical characteristics, treatment regimens, and prognosis of patients infected with 2019-nCoV during this outbreak. Methods: Clinical data from 137 2019-nCoV-infected patients admitted to the respiratory departments of nine tertiary hospitals in Hubei province from December 30, 2019 to January 24, 2020 were retrospectively collected, including general status, clinical manifestations, laboratory test results, imaging characteristics, and treatment regimens. Results: None of the 137 patients (61 males, 76 females, aged 20–83 years, median age 57 years) had a definite history of exposure to Huanan Seafood Wholesale Market. Major initial symptoms included fever (112/137, 81.8%), coughing (66/137, 48.2%), and muscle pain or fatigue (44/137, 32.1%), with other, less typical initial symptoms observed at low frequency, including heart palpitations, diarrhea, and headache. Nearly 80% of the patients had normal or decreased white blood cell counts, and 72.3% (99/137) had lymphocytopenia. Lung involvement was present in all cases, with most chest computed tomography scans showing lesions in multiple lung lobes, some of which were dense; ground-glass opacity co-existed with consolidation shadows or cord-like shadows. Given the lack of effective drugs, treatment focused on symptomatic and respiratory support. Immunoglobulin G was delivered to some critically ill patients according to their conditions. Systemic corticosteroid treatment did not show significant benefits. Notably, early respiratory support facilitated disease recovery and improved prognosis. The risk of death was primarily associated with age, underlying chronic diseases, and median interval from the appearance of initial symptoms to dyspnea. Conclusions: The majority of patients with 2019-nCoV pneumonia present with fever as the first symptom, and most of them still showed typical manifestations of viral pneumonia on chest imaging. Middle-aged and elderly patients with underlying comorbidities are susceptible to respiratory failure and may have a poorer prognosis.
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Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China
Huang, C., Wang, Y., Li, X., Ren, L., Zhao, J., Hu, Y., Zhang, L., Fan, G., Xu, J., Gu, X., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30183-5 · Cited by 48,884
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Cheung, K. S., Hung, I. F. N., Chan, P. P. Y., Lung, K. C., Tso, E., Liu, R., Ng, Y. Y., Chu, M. Y., Chung, T. W. H., Tam, A. R., et al. (2020) · Gastroenterology · doi:10.1053/j.gastro.2020.03.065 · Cited by 1,631
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Mao, R., Qiu, Y., He, J.-S., Tan, J.-Y., Li, X.-H., Liang, J., Shen, J., Zhu, L.-R., Chen, Y., Iacucci, M., et al. (2020) · The Lancet Gastroenterology & Hepatology · doi:10.1016/s2468-1253(20)30126-6 · Cited by 1,056
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Khera, A., Baum, S. J., Gluckman, T. J., Gulati, M., Martin, S. S., Michos, E. D., Navar, A. M., Taub, P. R., Toth, P. P., Virani, S. S., et al. (2020) · American Journal of Preventive Cardiology · doi:10.1016/j.ajpc.2020.100009 · Cited by 143
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Fong, T. K.-H., Cheung, T., Chan, W.-C., & Cheng, C. P.-W. (2021) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph19010184 · Cited by 41
Metadata
- Authors
- Liu, K., Fang, Y.-Y., Deng, Y., Liu, W., Wang, M.-F., Ma, J.-P., Xiao, W., Wang, Y.-N., Zhong, M.-H., Li, C.-H., Li, G.-C., & Liu, H.-G.
- Venue
- Chinese Medical Journal
- Published
- 2020-02-15
- Volume
- 133
- Issue
- 9
- Pages
- 1025-1031
- ISSN
- 0366-6999 (ISSN-L)
- 2542-5641
- OpenAlex
- W3006485704
- Cited by
- 1,411
- References
- 1
- FWCI
- 40.50
- Type
- journal article
- Language
- en
- Open access
- gold
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