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Predictors of mortality in patients with coronavirus disease 2019: a systematic review and meta-analysis.
- Source :
-
BMC infectious diseases [BMC Infect Dis] 2021 Jul 08; Vol. 21 (1), pp. 663. Date of Electronic Publication: 2021 Jul 08. - Publication Year :
- 2021
-
Abstract
- Background: Coronavirus disease 2019 (COVID-19) is associated with a high mortality rate, especially in patients with severe illness. We conducted a systematic review and meta-analysis to assess the potential predictors of mortality in patients with COVID-19.<br />Methods: PubMed, EMBASE, the Cochrane Library, and three electronic Chinese databases were searched from December 1, 2019 to April 29, 2020. Eligible studies reporting potential predictors of mortality in patients with COVID-19 were identified. Unadjusted prognostic effect estimates were pooled using the random-effects model if data from at least two studies were available. Adjusted prognostic effect estimates were presented by qualitative analysis.<br />Results: Thirty-six observational studies were identified, of which 27 were included in the meta-analysis. A total of 106 potential risk factors were tested, and the following important predictors were associated with mortality: advanced age, male sex, current smoking status, preexisting comorbidities (especially chronic kidney, respiratory, and cardio-cerebrovascular diseases), symptoms of dyspnea, complications during hospitalization, corticosteroid therapy and a severe condition. Additionally, a series of abnormal laboratory biomarkers of hematologic parameters, hepatorenal function, inflammation, coagulation, and cardiovascular injury were also associated with fatal outcome.<br />Conclusion: We identified predictors of mortality in patients with COVID-19. These findings could help healthcare providers take appropriate measures and improve clinical outcomes in such patients.
- Subjects :
- Adrenal Cortex Hormones administration & dosage
Age Distribution
Cardiovascular Diseases epidemiology
Comorbidity
Databases, Factual
Dyspnea epidemiology
Female
Hospitalization statistics & numerical data
Humans
Inflammation epidemiology
Kidney physiopathology
Liver physiopathology
Male
Observational Studies as Topic
Prognosis
Risk Factors
Sex Distribution
Smokers statistics & numerical data
COVID-19 diagnosis
COVID-19 mortality
Subjects
Details
- Language :
- English
- ISSN :
- 1471-2334
- Volume :
- 21
- Issue :
- 1
- Database :
- MEDLINE
- Journal :
- BMC infectious diseases
- Publication Type :
- Academic Journal
- Accession number :
- 34238232
- Full Text :
- https://doi.org/10.1186/s12879-021-06369-0