Profiling Covid-19 patients with respect to level of severity: an integrated statistical approach.

ABSTRACT: A full understanding of the characteristics of Covid-19 patients with a better chance of experiencing poor vital outcomes is critical for implementing accurate and precise treatments. In this paper, two different advanced data-driven statistical approaches along with standard statistical methods have been implemented to identify groups of patients most at-risk for death or severity of respiratory distress. First, the tree-based analysis allowed to identify profiles of patients with different risk of in-hospital death (by Survival Tree-ST analysis) and severity of respiratory distress (by Classification and Regression Tree-CART analysis), and to unravel the role on risk stratification of highly dependent covariates (i.e., demographic characteristics, admission values and comorbidities). The

SUBMITTER: Cugnata F 

PROVIDER: S-EPMC10071456 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature