A Survey for Predictors of Mortality among COVID-19 Patients: A Retrospective Study from Iran

Background and Objective: In the current COVID-19 pandemic, disease diagnosis is essential for optimal management and timely isolation of infected cases in order to prevent further spread. The aim of this study is to assess of predictors of mortality among COVID-19 patients. Material and Methods: In a retrospective study, 522 COVID-19 patients were enrolled in Razi hospital, Guilan Province, Iran. This hospital was the main center for the treatment of COVID-19 patients in Guilan province. Data gathering was performed by census sampling from March to August 2020. Simple and Multiple logistic regression analysis were applied to assess the relationships of clinical and demographic characteristics with in-hospital mortality. Results: Multiple logistic regression showed that older age (aOR=1.04, 95%CI: 1.02 to 1.06, P 0.001), decreased O2 saturation (aOR=0.89, 95%CI: 0.86 to 0.92, P 0.001), having a dysrhythmia (aOR=2.97, 95%CI: 1.46 to 6.05, P=0.003), symptoms associated with heart failure (aOR=0.43, 95%CI: 0.18 to 0.99, P=0.048), and mixed drug antiviruses (aOR=2.44, 95%CI: 1.22 to 4.90, P=0.012) were mortality predictor variables among COVID-19 patients. Conclusion: Therefore, special attention should be paid to the factors influencing the mortality of COVID-19 patients. It is recommended that older patients, dysrhythmia, and symptoms associated with heart failure be treated with extreme caution.