Risk Factor Analysis and Nomogram Construction for Non-Survivors among Critical Patients with COVID-19

Area of Science:

• Infectious Diseases
• Critical Care Medicine
• Epidemiology

Background:

• The COVID-19 pandemic, caused by SARS-CoV-2, emerged in late 2019, leading to significant global mortality.
• Identifying risk factors for death in critical COVID-19 patients is crucial for improving outcomes.

Purpose of the Study:

• To analyze risk factors associated with mortality in critical COVID-19 patients.
• To develop and validate a prognostic nomogram for predicting death risk in this population.

Main Methods:

• Retrospective analysis of clinical data from 104 critical COVID-19 patients at Zhongnan Hospital of Wuhan University.
• Univariable and multivariable logistic regression analyses to identify predictors of death.
• Construction and validation of a nomogram using identified risk factors: age, chest tightness, AST, and blood urea nitrogen.

Main Results:

• Age, chest tightness, AST, and blood urea nitrogen were identified as significant predictors of death in critical COVID-19 patients.
• The developed nomogram demonstrated high sensitivity (96.0%) and specificity (74.1%) in predicting mortality.
• The nomogram achieved an Area Under the Curve (AUC) of 0.893, indicating strong predictive accuracy.

Conclusions:

• Age, chest tightness, AST, and blood urea nitrogen are key prognostic indicators for critical COVID-19 patients.
• The validated nomogram serves as a valuable tool for assessing prognosis and guiding clinical management.
• This prognostic model can aid healthcare providers in risk stratification and resource allocation for critically ill COVID-19 patients.