Severity Patterns in COVID-19 Hospitalised Patients in Spain: I-MOVE-COVID-19 Study

Area of Science:

• Infectious Diseases
• Critical Care Medicine
• Epidemiology

Background:

• COVID-19 pandemic necessitated understanding risk factors for severe outcomes.
• Early identification of high-risk patients is crucial for effective management.

Purpose of the Study:

• To identify clinical factors associated with COVID-19 severity.
• To develop predictive models for mortality, ICU admission, and ventilation.

Main Methods:

• Multivariate analysis of clinical data from 2050 hospitalized patients.
• Development of nomograms for risk prediction.
• Retrospective cohort study design.

Main Results:

• Need for ventilation and ICU admission significantly increased death risk.
• Predictors of death included advanced age, thrombocytopenia, cancer, and elevated CPK.
• Symptoms like vomiting, sore throat, and cough were associated with reduced mortality risk.
• Need for ventilation was predicted by low oxygen saturation, diabetes, and obesity.
• ICU admission was predicted by need for ventilation and elevated LDH.

Conclusions:

• Clinical factors at admission can predict COVID-19 severity and outcomes.
• Findings can inform patient management and resource allocation.
• Predictive models can aid in strategic interventions against COVID-19.