Our study objective was to construct models using 20 routine laboratory parameters on admission to predict disease severity and mortality risk in a group of 254 hospitalized COVID-19 patients. Considering the influence of confounding factors in this single-center study, we also retrospectively assessed the correlations between the risk of death and the routine laboratory parameters within individual comorbidity subgroups. In multivariate regression models and by ROC curve analysis, a model of three routine laboratory parameters (AUC 0.85; 95% CI: 0.79–0.91) and a model of six laboratory factors (AUC 0.86; 95% CI: 0.81–0.91) were able to predict severity and mortality of COVID-19, respectively, compared with any other individual parameter. H...
Background: Several biomarkers and models have been proposed to predict in-hospital mortality among ...
BackgroundClinical utility of routinely measured serial biomarkers in predicting escalation of inpat...
Background: To identify and quantify associations between baseline characteristics on hospital admis...
Background. The rapid onset of a systemic pro-inflammatory state followed by acute respiratory distr...
Background: To determine the utility of admission laboratory markers in the assessment and prognosti...
Background: To determine the utility of admission laboratory markers in the assessment and prognosti...
Background: To determine the utility of admission laboratory markers in the assessment and prognosti...
Various scoring systems and cytokines have been cited as predicting disease severity in COVID-19 inf...
Background: To determine the utility of admission laboratory markers in the assessment and prognosti...
Background: To determine the utility of admission laboratory markers in the assessment and prognosti...
Introduction: Inflammation plays an important role in the basis of coronary artery diseases and thei...
Background: The coronavirus disease 2019 (COVID-19) has become a global pandemic, with 10%-20% of se...
Background: The potential significance of immunoinflammatory factors in the prognosis of individuals...
Systemic inflammation and hypercoagulopathy are known pathophysiological processes of coronavirus di...
Introduction: Predicting disease severity is important for treatment decisions in patients with COVI...
Background: Several biomarkers and models have been proposed to predict in-hospital mortality among ...
BackgroundClinical utility of routinely measured serial biomarkers in predicting escalation of inpat...
Background: To identify and quantify associations between baseline characteristics on hospital admis...
Background. The rapid onset of a systemic pro-inflammatory state followed by acute respiratory distr...
Background: To determine the utility of admission laboratory markers in the assessment and prognosti...
Background: To determine the utility of admission laboratory markers in the assessment and prognosti...
Background: To determine the utility of admission laboratory markers in the assessment and prognosti...
Various scoring systems and cytokines have been cited as predicting disease severity in COVID-19 inf...
Background: To determine the utility of admission laboratory markers in the assessment and prognosti...
Background: To determine the utility of admission laboratory markers in the assessment and prognosti...
Introduction: Inflammation plays an important role in the basis of coronary artery diseases and thei...
Background: The coronavirus disease 2019 (COVID-19) has become a global pandemic, with 10%-20% of se...
Background: The potential significance of immunoinflammatory factors in the prognosis of individuals...
Systemic inflammation and hypercoagulopathy are known pathophysiological processes of coronavirus di...
Introduction: Predicting disease severity is important for treatment decisions in patients with COVI...
Background: Several biomarkers and models have been proposed to predict in-hospital mortality among ...
BackgroundClinical utility of routinely measured serial biomarkers in predicting escalation of inpat...
Background: To identify and quantify associations between baseline characteristics on hospital admis...