Factors Associated with Mortality in Patients Hospitalized with COVID-19 Using Generalized Linear Model (Ordinal Logistic Regression) in North of Iran

Abstract

Background and purpose: Controlling the severity and death of the COVID-19 disease is still a major challenge. This research aimed at identifying the factors associated with mortality in hospitalized patients with COVID-19 applying generalized linear model. Materials and methods: In this cross-sectional study, demographic and clinical data of COVID-19 patients hospitalized with positive RT-PCR test results (n=6759) in Mazandaran hospitals (August 2019) were obtained from the national registration system for COVID-19. SPSS V27 and R V4.0 were used for data analyses and multivariate generalized linear model test with an ordinal logistic scale was applied. Results: Findings showed that full recovery and relative recovery occurred in 5888 (87.11%) and 400 (5.92%) patients, respectively. Mortality rate was 6.97%. The chance of death in patients with relative recovery (49.55%) compared with those with full recovery (21.61%) was almost 2.3 times higher. Predictors of mortality in these patients included age over 60 years (OR: 1.60), ICU admission (OR: 5.09), intubation (OR: 4.10), SpO2≤ 93% (OR: 2.41), cancer (OR: 1.74), diabetes (OR: 1.29), heart disease (OR: 1.41), and chronic kidney disease (OR: 2.17). Conclusion: Specific and timely medical care, considering the mentioned risk factors, should be introduced and provided to prevent mortality in patients hospitalized with COVID-19.

Keywords

• covid-19
• mortality
• risk factor
• odds ratio
• generalized linear model
• ordinal logistic