Development of a laboratory-based nomogram for predicting clinical outcomes in patients with severe COVID-19 undergoing glucocorticoid therapy.

ABSTRACT:

Background

While glucocorticoids remain cornerstone therapy for severe COVID-19, substantial heterogeneity persists in clinical outcomes. This single-center retrospective study sought to establish a predictive model integrating inflammatory biomarkers to guide risk stratification and personalized management.

Methods

We analysed 151 adults with WHO-defined severe COVID-19 receiving glucocorticoid therapy (December 2022-August 2023). Treatment non-response was defined as mortality during hospitalization, mechanical ventilation escalation, or persistent organ dysfunction. LASSO and logistic regression analyses identified predictors, with optimal biomarker thresholds determined using ROC curves. A nomogram was constructed and validated via split-sample testing (7:3 ratio) and 10

SUBMITTER: Xu L 

PROVIDER: S-EPMC12714636 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature