The DOI matches its Crossref record; 122 of the 122 references it cites were found in a registry or an index.
Predictors of COVID‐19 severity: A literature review
Open accessAbstract
Summary: The coronavirus disease 2019 (COVID‐19) pandemic is a rapidly evolving global emergency that continues to strain healthcare systems. Emerging research describes a plethora of patient factors—including demographic, clinical, immunologic, hematological, biochemical, and radiographic findings—that may be of utility to clinicians to predict COVID‐19 severity and mortality. We present a synthesis of the current literature pertaining to factors predictive of COVID‐19 clinical course and outcomes. Findings associated with increased disease severity and/or mortality include age > 55 years, multiple pre‐existing comorbidities, hypoxia, specific computed tomography findings indicative of extensive lung involvement, diverse laboratory test abnormalities, and biomarkers of end‐organ dysfunction. Hypothesis‐driven research is critical to identify the key evidence‐based prognostic factors that will inform the design of intervention studies to improve the outcomes of patients with COVID‐19 and to appropriately allocate scarce resources.
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Cites
Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China
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Clinical characteristics of coronavirus disease 2019 in China
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La certeza de lo impredecible: Cultura Educación y Sociedad en tiempos de COVID19
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Endothelial cell infection and endotheliitis in COVID-19
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Angiotensin-converting enzyme 2 is a functional receptor for the SARS coronavirus
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Cited by
Marrelli, M. (2021) · Plants · doi:10.3390/plants10071355 · Cited by 91
Wu, Y., Rocha, B. M., Kaimakamis, E., Cheimariotis, G.-A., Petmezas, G., Chatzis, E., Kilintzis, V., Stefanopoulos, L., Pessoa, D., Marques, A., et al. (2024) · Expert Systems with Applications · doi:10.1016/j.eswa.2023.121089 · Cited by 23
Kanayama, A., Tsuchihashi, Y., Otomi, Y., Enomoto, H., Arima, Y., Takahashi, T., Kobayashi, Y., Kaku, K., Sunagawa, T., Suzuki, M., et al. (2022) · Japanese Journal of Radiology · doi:10.1007/s11604-022-01300-2 · Cited by 7
Metadata
- Authors
- 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., Flanigan, T., & Michelow, I. C.
- Venue
- Reviews in Medical Virology
- Publisher
- Wiley
- Published
- 2020-07-30
- Volume
- 31
- Issue
- 1
- Pages
- 1-10
- ISSN
- 1052-9276 (ISSN-L)
- 1099-1654
- OpenAlex
- W3046496943
- Cited by
- 819
- References
- 122
- FWCI
- 19.10
- Type
- journal article
- Language
- en
- Open access
- green
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- 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., Flanigan, T., & Michelow, I. C. (2021). Predictors of COVID‐19 severity: A literature review. Reviews in Medical Virology. https://doi.org/10.1002/rmv.2146
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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