biostudies-literatureUnknown11(20)Poskurica M<h4>Background</h4>Early prediction of COVID-19 patients' mortality risk may be beneficial in adequate triage and risk assessment. Therefore, we aimed to single out the independent morality predictors of hospitalized COVID-19 patients among parameters available on hospital admission.<h4>Methods</h4>An observational, retrospective-prospective cohort study was conducted on 703 consecutive COVID-19 patients hospitalized in the University Clinical Center Kragujevac between September and December 2021. Patients were followed during the hospitalization, and in-hospital mortality was observed as a primary end-point. Within 24 h of admission, patients were sampled for blood gas and laboratory analysis, including complete blood cell count, inflammation biomarkers and other biochemistry, coagulation parameters, and cardiac biomarkers. Socio-demographic and medical history data were obtained using patients' medical records.<h4>Results</h4>The overall prevalence of mortality was 28.4% (<i>n =</i> 199). After performing multiple regression analysis on 20 parameters, according to the initial univariate analysis, only four independent variables gave statistically significant contributions to the model: SaO2 &lt; 88.5 % (aOR 3.075), IL-6 <i>&gt;</i> 74.6 pg/mL (aOR 2.389), LDH <i>&gt;</i> 804.5 U/L (aOR 2.069) and age &gt; 69.5 years (aOR 1.786). The C-index of the predicted probability calculated using this multivariate logistic model was 0.740 (<i>p &lt;</i> 0.001).<h4>Conclusions</h4>Parameters available on hospital admission can be beneficial in predicting COVID-19 mortality.Journal of clinical medicine6109https://www.ebi.ac.uk/biostudies/studies/S-EPMC9605560biostudies-literatureAdmission Predictors of Mortality in Hospitalized COVID-19 Patients-A Serbian Cohort Study.PMC9605560Poskurica MCekerevac ILazarevic SCupurdija VMarkovic MNikolic TPopovic MStevanovic ĐJevtovic AAnđelkovic MAzanjac Arsic AZdravkovic VJovanovic MZdravkovic NPatrnogic APetrovic MVesic KfalseAdmission Predictors of Mortality in Hospitalized COVID-19 Patients-A Serbian Cohort Study.<h4>Background</h4>Early prediction of COVID-19 patients' mortality risk may be beneficial in adequate triage and risk assessment. Therefore, we aimed to single out the independent morality predictors of hospitalized COVID-19 patients among parameters available on hospital admission.<h4>Methods</h4>An observational, retrospective-prospective cohort study was conducted on 703 consecutive COVID-19 patients hospitalized in the University Clinical Center Kragujevac between September and December 2021. Patients were followed during the hospitalization, and in-hospital mortality was observed as a primary end-point. Within 24 h of admission, patients were sampled for blood gas and laboratory analysis, including complete blood cell count, inflammation biomarkers and other biochemistry, coagulation parameters, and cardiac biomarkers. Socio-demographic and medical history data were obtained using patients' medical records.<h4>Results</h4>The overall prevalence of mortality was 28.4% (<i>n =</i> 199). After performing multiple regression analysis on 20 parameters, according to the initial univariate analysis, only four independent variables gave statistically significant contributions to the model: SaO2 &lt; 88.5 % (aOR 3.075), IL-6 <i>&gt;</i> 74.6 pg/mL (aOR 2.389), LDH <i>&gt;</i> 804.5 U/L (aOR 2.069) and age &gt; 69.5 years (aOR 1.786). The C-index of the predicted probability calculated using this multivariate logistic model was 0.740 (<i>p &lt;</i> 0.001).<h4>Conclusions</h4>Parameters available on hospital admission can be beneficial in predicting COVID-19 mortality.2022-01-01T00:00:00Z2022 Oct2025-04-18T21:21:20.733Z2025-04-07T09:14:56.592ZS-EPMC96055603629443010.3390/jcm11206109