Multimarker Approach: An Effective Tool in the Risk Stratification of Patients Admitted to the Emergency Department

Background: The use of biomarkers in emergency room decision-making has significantly increased, particularly during the COVID-19 pandemic, due to urgent clinical needs. SARS-CoV-2 infection presents a spectrum of symptoms, from asymptomatic cases to severe pneumonia with respiratory failure. During the pandemic, various prognostic tools and biomarkers have been used to quickly guide patients to appropriate care upon admission. This study evaluated the effectiveness of a multimarker approach for early risk stratification of patients with confirmed SARS-CoV-2 infection in the Emergency Department. It aimed to determine if a combined biomarker panel could better predict COVID-19 severity than single biomarkers, aiding in clinical decision-making and resource management. Methods: This retrospective observational study analyzed data from 265 patients with suspected COVID-19 admitted to the Emergency Department at the University Hospital Tor Vergata in Rome from April to December 2020. SARS-CoV-2 infection was confirmed by RT-PCR swabs. Clinical features and biomarker levels were analyzed, and mortality prediction was assessed using ROC curve analysis to determine the AUC. Results: Results demonstrated that the predictive power for mortality increased when multiple biomarkers were considered together. The most comprehensive panel, combining MR-proADM, CRP, D-dimer, LDH, and CT score, achieved the highest accuracy (AUC: 0.866), outperforming any individual marker. Conclusion: Combining multiple biomarkers improved the prediction of disease severity over individual biomarkers. These findings suggest that using a comprehensive biomarker panel can more accurately predict SARS-CoV-2 severity, supporting its potential utility for early risk stratification in various emergency settings and aiding in the efficient allocation of healthcare resources.