The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Risk Factors Associated With Clinical Outcomes in 323 Coronavirus Disease 2019 (COVID-19) Hospitalized Patients in Wuhan, China
Open accessAbstract
Background: With evidence of sustained transmission in more than 190 countries, coronavirus disease 2019 (COVID-19) has been declared a global pandemic. Data are urgently needed about risk factors associated with clinical outcomes. Methods: A retrospective review of 323 hospitalized patients with COVID-19 in Wuhan was conducted. Patients were classified into 3 disease severity groups (nonsevere, severe, and critical), based on initial clinical presentation. Clinical outcomes were designated as favorable and unfavorable, based on disease progression and response to treatments. Logistic regression models were performed to identify risk factors associated with clinical outcomes, and log-rank test was conducted for the association with clinical progression. Results: Current standard treatments did not show significant improvement in patient outcomes. By univariate logistic regression analysis, 27 risk factors were significantly associated with clinical outcomes. Multivariate regression indicated age >65 years (P < .001), smoking (P = .001), critical disease status (P = .002), diabetes (P = .025), high hypersensitive troponin I (>0.04 pg/mL, P = .02), leukocytosis (>10 × 109/L, P < .001), and neutrophilia (>75 × 109/L, P < .001) predicted unfavorable clinical outcomes. In contrast, the administration of hypnotics was significantly associated with favorable outcomes (P < .001), which was confirmed by survival analysis. Conclusions: Hypnotics may be an effective ancillary treatment for COVID-19. We also found novel risk factors, such as higher hypersensitive troponin I, predicted poor clinical outcomes. Overall, our study provides useful data to guide early clinical decision making to reduce mortality and improve clinical outcomes of COVID-19.
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Clinical characteristics of coronavirus disease 2019 in China
Guan, W.-J., Ni, Z.-Y., Hu, Y., Liang, W.-H., Ou, C.-Q., He, J.-X., Liu, L., Shan, H., Lei, C.-L., Hui, D. S. C., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2002032 · Cited by 30,246
Self-citationA novel coronavirus from patients with pneumonia in China, 2019
Zhu, N., Zhang, D., Wang, W., Li, X., Yang, B., Song, J., Zhao, X., Huang, B., Shi, W., Lu, R., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2001017 · Cited by 28,244
Zhou, F., Yu, T., Du, R., Fan, G., Liu, Y., Liu, Z., Xiang, J., Wang, Y., Song, B., Gu, X., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30566-3 · Cited by 27,263
Self-citationChen, N., Zhou, M., Dong, X., Qu, J., Gong, F., Han, Y., Qiu, Y., Wang, J., Liu, Y., Wei, Y., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30211-7 · Cited by 21,415
Self-citationEarly transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia
Li, Q., Guan, X., Wu, P., Wang, X., Zhou, L., Tong, Y., Ren, R., Leung, K. S. M., Lau, E. H. Y., Wong, J. Y., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2001316 · Cited by 16,575
Self-citationSterne, J. A. C., White, I. R., Carlin, J. B., Spratt, M., Royston, P., Kenward, M. G., Wood, A. M., & Carpenter, J. R. (2009) · BMJ · doi:10.1136/bmj.b2393 · Cited by 7,299
A crucial role of angiotensin converting enzyme 2 (ACE2) in SARS coronavirus–induced lung injury
Kuba, K., Imai, Y., Rao, S., Gao, H., Guo, F., Guan, B., Huan, Y., Yang, P., Zhang, Y., Deng, W., et al. (2005) · Nature Medicine · doi:10.1038/nm1267 · Cited by 3,445
Self-citationClinical Characteristics of Covid-19 in New York City
Goyal, P., Choi, J. J., Pinheiro, L. C., Schenck, E. J., Chen, R., Jabri, A., Satlin, M. J., Campion, T. R., Nahid, M., Ringel, J. B., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmc2010419 · Cited by 2,234
Self-citationTissue factor as a link between inflammation and coagulation
Witkowski, M., Landmesser, U., & Rauch, U. (2016) · Trends in Cardiovascular Medicine · doi:10.1016/j.tcm.2015.12.001 · Cited by 240
SARS-CoV-2 Infection among Travelers Returning from Wuhan, China
Ng, O.-T., Marimuthu, K., Chia, P.-Y., Koh, V., Chiew, C. J., De Wang, L., Young, B. E., Chan, M., Vasoo, S., Ling, L.-M., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmc2003100 · Cited by 130
Cited by
Popkin, B. M., Du, S., Green, W. D., Beck, M. A., Algaith, T., Herbst, C. H., Alsukait, R. F., Alluhidan, M., Alazemi, N., & Shekar, M. (2020) · Obesity Reviews · doi:10.1111/obr.13128 · Cited by 1,150
Predictors of COVID‐19 severity: A literature review
Gallo Marin, B., Aghagoli, G., Lavine, K., Yang, L., Siff, E. J., Chiang, S. S., Salazar‐Mather, T. P., Dumenco, L., Savaria, M. C., Aung, S. N., et al. (2021) · Reviews in Medical Virology · doi:10.1002/rmv.2146 · Cited by 819
Lim, Z. J., Subramaniam, A., Ponnapa Reddy, M., Blecher, G., Kadam, U., Afroz, A., Billah, B., Ashwin, S., Kubicki, M., Bilotta, F., et al. (2021) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/rccm.202006-2405oc · Cited by 369
Pranata, R., Lim, M. A., Huang, I., Raharjo, S. B., & Lukito, A. A. (2020) · Journal of the Renin-Angiotensin-Aldosterone System · doi:10.1177/1470320320926899 · Cited by 346
Clinical determinants of the severity of COVID-19: A systematic review and meta-analysis
Li, X., Zhong, X., Wang, Y., Zeng, X., Luo, T., & Liu, Q. (2021) · PLOS ONE · doi:10.1371/journal.pone.0250602 · Cited by 236
Metadata
- Authors
- Hu, L., Chen, S., Fu, Y., Gao, Z., Long, H., Ren, H.-W., Zuo, Y., Wang, J., Li, H., Xu, Q.-B., Yu, W.-X., Liu, J., Shao, C., Hao, J.-J., Wang, C.-Z., Ma, Y., Wang, Z., Yanagihara, R., & Deng, Y.
- Venue
- Clinical Infectious Diseases
- Publisher
- Oxford University Press (OUP)
- Published
- 2020-05-03
- Volume
- 71
- Issue
- 16
- Pages
- 2089-2098
- ISSN
- 1058-4838 (ISSN-L)
- 1537-6591
- OpenAlex
- W3023831293
- Cited by
- 392
- References
- 11
- FWCI
- 10.71
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Hu, L., Chen, S., Fu, Y., Gao, Z., Long, H., Ren, H.-W., Zuo, Y., Wang, J., Li, H., Xu, Q.-B., Yu, W.-X., Liu, J., Shao, C., Hao, J.-J., Wang, C.-Z., Ma, Y., Wang, Z., Yanagihara, R., & Deng, Y. (2020). Risk Factors Associated With Clinical Outcomes in 323 Coronavirus Disease 2019 (COVID-19) Hospitalized Patients in Wuhan, China. Clinical Infectious Diseases. https://doi.org/10.1093/cid/ciaa539
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