Basic Predictive Risk Factors for Cytokine Storms in COVID-19 Patients

Area of Science:

• Immunology
• Infectious Diseases
• Critical Care Medicine

Background:

• Immune dysregulation and cytokine storm (CS) are key in severe COVID-19 pathogenesis.
• Early identification of patients at risk for CS is vital for timely intervention.
• Existing prognostic tools may not fully capture the complexity of CS development in COVID-19.

Purpose of the Study:

• To identify prognostic biomarkers for cytokine storm (CS) development in coronavirus disease 2019 (COVID-19) patients.
• To integrate these biomarkers into a practical prognostic score for routine clinical use.
• To facilitate early detection and management of severe COVID-19 cases associated with CS.

Main Methods:

• Retrospective review of 458 COVID-19 patient records.
• Utilized clinical assessment, chest CT scans, ECG, and laboratory tests (ferritin, CRP, IL-6, LDH, D-dimer).
• Incorporated the National Early Warning Score (NEWS) and its dynamics.

Main Results:

• Key risk factors for CS include male gender, age >40, positive SARS-CoV-2 RNA, low lymphocyte count, NEWS score dynamics, LDH, D-dimer, ferritin, and IL-6.
• A prognostic scale incorporating NEWS score dynamics, IL-6, CRP, lymphocyte count, SARS-CoV-2 RNA status, and age was developed.
• This scale effectively identifies patients at high risk for cytokine storm.

Conclusions:

• The developed prognostic score is a valuable tool for identifying COVID-19 patients at high risk of cytokine storm.
• Early identification enables timely initiation of anti-inflammatory therapy.
• Biomarkers such as NEWS score dynamics, IL-6, and CRP levels are crucial for monitoring CS risk.