Risk Factors Analysis for Rapid In-Hospital Mortality among Covid-19 Patients in a Tertiary Care Hospital in Indonesia - Febriawati, Juwita; Putra, Ngakan Putu Parsama; Listyoko, Aditya Sri; Djajalaksana, Susanthy (Fakultas Kedokteran Universitas Brawijaya, 2024)
Systemic inflammation plays an important role in pathogenesis of Covid-19, especially in development of ARDS which is characterized by decrease of PaO2/FiO2 ratio. CRP and procalcitonin are inflammatory markers that are closely associated with severity and mortality of Covid-19. Although several studies have addressed benefit of CRP and procalcitonin as markers on Covid-19 severity, the benefit of these inflammatory markers for in-hospital mortality remain inadequately understood. The aim of this study was to analyze PaO2/FiO2 ratio,comorbidity,CRP,and procalcitonin as risk factors that affect time of in-hospital mortality Covid-19 patient. This was a retrospective observational cohort study of 250 Covid-19 patients who died during hospitalization and data was retrieved from medical record. Laboratory data was collected from three different times, including at time of admission,third day of hospital care,and before patient’s death. Data were analyzed using Chi square test,Mann Whitney test,Wilcoxon test, Friedman test, and binary logistic regresion. There were significant differences between CRP and procalcitonin at admission and time of in-hospital mortality (p<0.001; p=0.007). Binary logistic regression analysis revealed significant relationship between CRP and time of in-hospital mortality with p=0.007. ROC curve showed optimal threshold of 11.75mg/L with sensitivity 72.3%; specificity 59.6%, RR 3.24(95% CI: 1.84-5.70). Significant changes were observed regarding PaO2/FiO2 ratio,CRP,and procalcitonin at admission as compared to before patient’s death with p<0.001;p=0.017;p<0.001 respectively. This study showed significant decrease of PaO2/FiO2 ratio, elevated CRP and procalcitonin at admission as compared to before patient’s death. The increase of CRP could serve as predictor for time of in-hospital mortality for Covid-19 patient.