Predictors of COVID‐19 severity: A literature review
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—t...
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| Vydané v: | Reviews in medical virology Ročník 31; číslo 1; s. 1 - 10 |
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| Hlavní autori: | , , , , , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
England
Wiley Periodicals Inc
01.01.2021
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| Predmet: | |
| ISSN: | 1052-9276, 1099-1654, 1099-1654 |
| On-line prístup: | Získať plný text |
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| Abstract | 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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| AbstractList | 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.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. 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. 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. |
| Author | Yang, Lanbo Flanigan, Timothy Michelow, Ian C. Gallo Marin, Benjamin Aghagoli, Ghazal Chiang, Silvia S. Siff, Emily J. Dumenco, Luba Lavine, Katya Savaria, Michael C Aung, Su N. Salazar‐Mather, Thais P. |
| AuthorAffiliation | 4 Center for International Health Research, Rhode Island Hospital, Providence, Rhode Island 3 Department of Pediatrics, Division of Infectious Diseases, Warren Alpert Medical School of Brown University, Providence, Rhode Island 5 Office of Medical Education and Continuous Quality Improvement, Warren Alpert Medical School of Brown University, Providence, Rhode Island 6 Department of Medicine, Division of Infectious Diseases, Warren Alpert Medical School of Brown University, Providence, Rhode Island 1 Warren Alpert Medical School of Brown University, Providence, Rhode Island 2 Department of Cognitive, Linguistic, & Psychological Sciences, Brown University, Providence, Rhode Island |
| AuthorAffiliation_xml | – name: 6 Department of Medicine, Division of Infectious Diseases, Warren Alpert Medical School of Brown University, Providence, Rhode Island – name: 3 Department of Pediatrics, Division of Infectious Diseases, Warren Alpert Medical School of Brown University, Providence, Rhode Island – name: 2 Department of Cognitive, Linguistic, & Psychological Sciences, Brown University, Providence, Rhode Island – name: 1 Warren Alpert Medical School of Brown University, Providence, Rhode Island – name: 5 Office of Medical Education and Continuous Quality Improvement, Warren Alpert Medical School of Brown University, Providence, Rhode Island – name: 4 Center for International Health Research, Rhode Island Hospital, Providence, Rhode Island |
| Author_xml | – sequence: 1 givenname: Benjamin orcidid: 0000-0003-4877-354X surname: Gallo Marin fullname: Gallo Marin, Benjamin email: ben_gallo@brown.edu organization: Warren Alpert Medical School of Brown University – sequence: 2 givenname: Ghazal surname: Aghagoli fullname: Aghagoli, Ghazal organization: Warren Alpert Medical School of Brown University – sequence: 3 givenname: Katya surname: Lavine fullname: Lavine, Katya organization: Warren Alpert Medical School of Brown University – sequence: 4 givenname: Lanbo surname: Yang fullname: Yang, Lanbo organization: Warren Alpert Medical School of Brown University – sequence: 5 givenname: Emily J. surname: Siff fullname: Siff, Emily J. organization: Brown University – sequence: 6 givenname: Silvia S. surname: Chiang fullname: Chiang, Silvia S. organization: Rhode Island Hospital – sequence: 7 givenname: Thais P. surname: Salazar‐Mather fullname: Salazar‐Mather, Thais P. organization: Office of Medical Education and Continuous Quality Improvement, Warren Alpert Medical School of Brown University – sequence: 8 givenname: Luba surname: Dumenco fullname: Dumenco, Luba organization: Office of Medical Education and Continuous Quality Improvement, Warren Alpert Medical School of Brown University – sequence: 9 givenname: Michael C surname: Savaria fullname: Savaria, Michael C organization: Warren Alpert Medical School of Brown University – sequence: 10 givenname: Su N. surname: Aung fullname: Aung, Su N. organization: Warren Alpert Medical School of Brown University – sequence: 11 givenname: Timothy surname: Flanigan fullname: Flanigan, Timothy organization: Warren Alpert Medical School of Brown University – sequence: 12 givenname: Ian C. surname: Michelow fullname: Michelow, Ian C. organization: Rhode Island Hospital |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/32845042$$D View this record in MEDLINE/PubMed |
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The coronavirus disease 2019 (COVID‐19) pandemic is a rapidly evolving global emergency that continues to strain healthcare systems. Emerging research... The coronavirus disease 2019 (COVID‐19) pandemic is a rapidly evolving global emergency that continues to strain healthcare systems. Emerging research... The coronavirus disease 2019 (COVID-19) pandemic is a rapidly evolving global emergency that continues to strain healthcare systems. Emerging research... |
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| SubjectTerms | Adult Aging Biomarkers Child Comorbidity Computed tomography Coronaviruses COVID-19 COVID-19 - mortality COVID-19 - pathology COVID-19 - transmission Humans Hypoxia Hypoxia - pathology Literature reviews Mortality Pandemics predictors Prognosis SARS-CoV-2 - pathogenicity SARS‐CoV‐2 severity Severity of Illness Index |
| Title | Predictors of COVID‐19 severity: A literature review |
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