Background: Identification of reliable outcome predictors in coronavirus disease 2019 (COVID-19) is of paramount importance for improving patient's management. Methods: A systematic review of literature was conducted until 24 April 2020. From 6843 articles, 49 studies were selected for a pooled assessment; cumulative statistics for age and sex were retrieved in 587 790 and 602 234 cases. Two endpoints were defined: (a) a composite outcome including death, severe presentation, hospitalization in the intensive care unit (ICU) and/or mechanical ventilation; and (b) in-hospital mortality. We extracted numeric data on patients’ characteristics and cases with adverse outcomes and employed inverse variance random-effects models to derive pooled estimates. Results: We identified 18 and 12 factors associated with the composite endpoint and death, respectively. Among those, a history of CVD (odds ratio (OR) = 3.15, 95% confidence intervals (CIs) 2.26-4.41), acute cardiac (OR = 10.58, 5.00-22.40) or kidney (OR = 5.13, 1.78-14.83) injury, increased procalcitonin (OR = 4.8, 2.034-11.31) or D-dimer (OR = 3.7, 1.74-7.89), and thrombocytopenia (OR = 6.23, 1.031-37.67) conveyed the highest odds for the adverse composite endpoint. Advanced age, male sex, cardiovascular comorbidities, acute cardiac or kidney injury, lymphocytopenia and D-dimer conferred an increased risk of in-hospital death. With respect to the treatment of the acute phase, therapy with steroids was associated with the adverse composite endpoint (OR = 3.61, 95% CI 1.934-6.73), but not with mortality. Conclusions: Advanced age, comorbidities, abnormal inflammatory and organ injury circulating biomarkers captured patients with an adverse clinical outcome. Clinical history and laboratory profile may then help identify patients with a higher risk of in-hospital mortality.
ASJC Scopus subject areas
- Clinical Biochemistry