Oxidative Stress Markers and Prediction of Severity With a Machine Learning Approach in Hospitalized Patients With COVID-19 and Severe Lung Disease: Observational, Retrospective, Single-Center Feasibility Study.
Journal:
JMIR formative research
PMID:
40215478
Abstract
BACKGROUND: Serious pulmonary pathologies of infectious, viral, or bacterial origin are accompanied by inflammation and an increase in oxidative stress (OS). In these situations, biological measurements of OS are technically difficult to obtain, and their results are difficult to interpret. OS assays that do not require complex preanalytical methods, as well as machine learning methods for improving interpretation of the results, would be very useful tools for medical and care teams.