Factors Associated With COVID-۱۹- related Death Using Logistic Regression

Background and Objective: Knowing demographic and clinical characteristics of death cases due to COVID-۱۹ can helps in early identification of critically ill patients, thereby reducing mortality (۱, ۲). To understand the characteristics of patients who die of COVID-۱۹, we evaluated the outcome of ۷۴۹ COVID-۱۹ confirmed cases.Materials and Methods: In this study, we included all laboratory-confirmed COVID-۱۹ cases with known treatment outcomes in Hamadan province, Iran, between Feb ۲۰, ۲۰۲۰, to May ۱۰, ۲۰۲۰. Demographic, clinical, laboratory data and treatment outcomes were extracted from electronic medical records and compared between survived cases and patients with death outcome. Univariable and multivariable logistic regression model were used to determine the predictors of death.Findings: From ۷۴۹ investigated patients, ۷۷ patients (۱۰.۲۸%) were died during the treatment. The mean age of patients was ۵۳.۹۷±۱۹.۰۴ years. Multivariable logistic regression showed that males had ۲.۰۷ fold higher odds of death (P=۰.۰۰۷). Those with ۶۰ years old and more had ۶.۴۹ fold higher odds of death (P=۰.۰۰۱). Patients with an underlying disease had ۷.۱۴ fold higher odds of death (P<۰.۰۰۱) and patients who were hospitalized in the ICU ward had ۲.۲۴ times higher odds of COVID-۱۹ related mortality (P=۰.۰۰۵). Conclusion: We found that male gender, older age, and having an underlying disease are associated with increase the COVID-۱۹- related Death Which is consistent with the findings of other studies (۳-۵). These findings could help physicians to identify patients with poor prognosis at an early stage and better management of them.

کلیدواژه ها:

Risk factor ، Covid-۱۹ ، Epidemiology ، Death ، Iran