A brief-review of the risk factors for covid-19 severity
Bibliographic Data
| ID | 14458337 |
|---|---|
| Authors | J E Rod (0000-0002-1584-1983, Queensland University of Technology), Oscar Oviedo-Trespalacios (0000-0001-5916-3996, Queensland University of Technology), Javier Cortes-Ramirez (0000-0002-5876-165X, Queensland University of Technology) |
| Year | 2020 |
| Volume | 54 |
| Pages | 60 |
| Publication date | 2020-07-10 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Revista de Saúde Pública (JOURNAL) |
| Journal identifiers | ISSN: 0034-8910 • E-ISSN: 0034-8910 |
| Publisher | Universidade de São Paulo. Agência de Bibliotecas e Coleções Digitais (PUBLISHER) |
| DOI | 10.11606/s1518-8787.2020054002481 |
| PMID | 32491116 |
| OpenAlex | W3030870282 |
| Language | EN |
| Citations received | 11 |
| References cited | 7 |
The World Health Organization has emphasized that one of the most important questions to address regarding the covid-19 pandemic is to understand risk factors for disease severity. We conducted a brief review that synthesizes the available evidence and provides a judgment on the consistency of the association between risk factors and a composite end-point of severe-fatal covid-19. Additionally, we also conducted a comparability analysis of risk factors across 17 studies. We found evidence supporting a total of 60 predictors for disease severity, of which seven were deemed of high consistency, 40 of medium and 13 of low. Among the factors with high consistency of association, we found age, C-reactive protein, D-dimer, albumin, body temperature, SOFA score and diabetes. The results suggest that diabetes might be the most consistent comorbidity predicting disease severity and that future research should carefully consider the comparability of reporting cases, factors, and outcomes along the different stages of the natural history of covid-19
2019-20 coronavirus outbreak · Comorbidity · Comparability · Consistency (knowledge bases) · Coronavirus disease 2019 (COVID-19) · Diabetes mellitus · Disease · Infectious disease (medical specialty) · Outbreak · Pandemic · Pathology · Computer Science · COVID-19 Clinical Research Studies · Internal Medicine · Long-Term Effects of COVID-19 · Medicine · SARS-CoV-2 and COVID-19 Research
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| Citations per year | 1.83 |
|---|---|
| Citation span | 2020 - 2025 (6) |
| Highly cited | No |