Identifying Key Hematological and Biochemical Indicators of Disease Severity in COVID-19 and Non-COVID-19 Patients

Citations

WEB OF SCIENCE

1
Citations

SCOPUS

1

초록

Background: This study investigated hematological and biochemical parameters, including cell population data (CPD), to evaluate their association with severity in COVID-19 and non-COVID-19 patients. Identifying these parameters could aid in disease monitoring and clinical decision-making. Methods: A retrospective analysis of 8401 patients, including 603 COVID-19 cases and 7546 non-COVID-19 cases, were conducted. Complete blood count (CBC) and routine chemistry results obtained near the time of real-time polymerase chain reaction testing were analyzed to assess their associations with disease severity. A matched cohort analysis was performed to adjust for potential confounding factors, such as age and sex. Results: COVID-19 patients with elevated neutrophil side fluorescence light (NE-SFL), platelet-to-lymphocyte ratio (PLR), glucose, and aspartate aminotransferase (AST), along with decreased plateletcrit, were more likely to experience severe outcomes, such as hospitalization or death. In addition, decreased hemoglobin, lymphocyte side scatter (LY-SSC), and albumin, as well as increased leukocyte and monocyte side scatter (MO-SSC), were associated with a greater severity, regardless of COVID-19 status. Conclusions: We identified hematologic and chemical assay biomarkers that correlate with severe COVID-19. These findings may provide important information regarding the disease progression and clinical management. Incorporating these biomarkers into clinical decision support systems could facilitate personalized treatment strategies, optimize resource allocation, and enable real-time severity stratification.

키워드

COVID-19hematologic biomarkerseveritycell population dataprognosis
제목
Identifying Key Hematological and Biochemical Indicators of Disease Severity in COVID-19 and Non-COVID-19 Patients
저자
Kim, Soo-KyungPak, DaewooLee, Jong-HanRyu, Sook Won
DOI
10.3390/diagnostics15111374
발행일
2025-05-29
유형
Article
저널명
DIAGNOSTICS
15
11