Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 1 de 1
Filter
Add filters

Database
Main subject
Language
Document Type
Year range
1.
Int J Mol Sci ; 23(18)2022 Sep 09.
Article in English | MEDLINE | ID: covidwho-2010126

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 × 109/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.


Subject(s)
COVID-19 , Biomarkers , Creatinine , Hospital Mortality , Humans , Interleukin-6 , Pandemics , ROC Curve , Retrospective Studies , Urea
SELECTION OF CITATIONS
SEARCH DETAIL