Abstract
The COVID-19 pandemic poses global healthcare challenges due to its unpredictable clinical course. The aim of this study is to identify inflammatory biomarkers and other routine laboratory parameters associated with in-hospital mortality in critical COVID-19 patients. We performed a retrospective observational study on 117 critical COVID-19 patients. Following descriptive statistical analysis of the survivor and non-survivor groups, optimal cut-off levels for the statistically significant parameters were determined using the ROC method, and the corresponding Kaplan-Meier survival curves were calculated. The inflammatory parameters that present statistically significant differences between survivors and non-survivors are IL-6 ( p = 0.0004, cut-off = 27.68 pg/mL), CRP ( p = 0.027, cut-off = 68.15 mg/L) and IL-6/Ly ratio ( p = 0.0003, cut-off = 50.39). Additionally, other statistically significant markers are creatinine ( p = 0.031, cut-off = 0.83 mg/dL), urea ( p = 0.0002, cut-off = 55.85 mg/dL), AST ( p = 0.0209, cut-off = 44.15 U/L), INR ( p = 0.0055, cut-off = 1.075), WBC ( p = 0.0223, cut-off = 11.68 × 10 9 /L) and pH ( p = 0.0055, cut-off = 7.455). A survival analysis demonstrated significantly higher in-hospital mortality rates of patients with values of IL-6, IL-6/Ly, AST, INR, and pH exceeding previously mentioned thresholds. In our study, IL-6 and IL-6/Ly have a predictive value for the mortality of critically-ill patients diagnosed with COVID-19. The integration of these parameters with AST, INR and pH could contribute to a prognostic score for the risk stratification of critical patients, reducing healthcare costs and facilitating clinical decision-making.
Keywords: COVID-19; IL-6; inflammation.
【저자키워드】 COVID-19, IL-6, Inflammation., 【초록키워드】 Inflammation, Mortality, COVID-19 pandemic, CRP, risk stratification, Clinical course, survival, ROC, healthcare, Patient, AST, WBC, prognostic, Critical, patients, in-hospital mortality, marker, Inflammatory biomarker, retrospective, creatinine, Analysis, statistical analysis, Predictive, urea, in-hospital mortality rate, statistically significant difference, cut-off, critical COVID-19 patients, thresholds, global healthcare, survivor, parameter, laboratory parameter, non-survivor, Kaplan-Meier survival curve, identify, performed, calculated, contribute, reducing, demonstrated, significantly higher, groups, statistically significant, diagnosed with COVID-19, inflammatory parameter, INR,