Redefining COVID-19 Severity and Prognosis: The Role of Clinical and Immunobiotypes.

ABSTRACT:

Background

Most of the explanatory and prognostic models of COVID-19 lack of a comprehensive assessment of the wide COVID-19 spectrum of abnormalities. The aim of this study was to unveil novel biological features to explain COVID-19 severity and prognosis (death and disease progression).

Methods

A predictive model for COVID-19 severity in 121 patients was constructed by ordinal logistic regression calculating odds ratio (OR) with 95% confidence intervals (95% CI) for a set of clinical, immunological, metabolomic, and other biological traits. The accuracy and calibration of the model was tested with the area under the curve (AUC), Somer's D, and calibration plot. Hazard ratios with 95% CI for adverse outcomes were calculated with a Cox proportional-hazards model.

Results<

SUBMITTER: Torres-Ruiz J 

PROVIDER: S-EPMC8456081 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature