Predictive biomarkers of mortality in patients with severe COVID-19 hospitalized in intensive care unit

Front Immunol. 2024 Aug 30:15:1416715. doi: 10.3389/fimmu.2024.1416715. eCollection 2024.

Abstract

Objectives: This study was performed to identify predictive markers of worse outcomes in patients with severe COVID-19 in an intensive care unit.

Methods: Sixty patients with severe COVID-19, hospitalized in the Intensive Care Unit (ICU) between March and July 2021, were stratified into two groups according to the outcome survivors and non-survivors. After admission to the ICU, blood samples were collected directly for biomarker analysis. Routine hematological and biochemical biomarkers, as well as serum levels of cytokines, chemokines, and immunoglobulins, were investigated.

Results: Lymphopenia, neutrophilia, and thrombocytopenia were more pronounced in non-surviving patients, while the levels of CRP, AST, creatinine, ferritin, AST, troponin I, urea, magnesium, and potassium were higher in the non-surviving group than the survival group. In addition, serum levels of IL-10, CCL2, CXCL9, and CXCL10 were significantly increased in patients who did not survive. These changes in the biomarkers evaluated were associated with increased mortality in patients with severe COVID-19.

Conclusion: The present study confirmed and expanded the validity of laboratory biomarkers as indicators of mortality in severe COVID-19.

Keywords: COVID-19; SARS-CoV-2; chemokines; critically ill patient; cytokines; intensive care unit.

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Biomarkers* / blood
  • COVID-19* / blood
  • COVID-19* / immunology
  • COVID-19* / mortality
  • Cytokines / blood
  • Female
  • Hospitalization
  • Humans
  • Intensive Care Units*
  • Male
  • Middle Aged
  • Prognosis
  • SARS-CoV-2*
  • Severity of Illness Index

Substances

  • Biomarkers
  • Cytokines

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This study was funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project number (PNURSP2024R386), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia. This work was supported by the Financier of Studies and Projects/Ministério da Ciência, Tecnologia e Inovação (FINEP/MCTI) [No.01.20.0026.03], and in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) – code financing 001.