Time to death and its predictors among adult patients with COVID-19: A retrospective cohort study in Ethiopia - Atamenta, Tegene; Cherie, Amsale; Alemu, Wudma (Frontiers in Epidemiology, 2023)
Background Coronavirus (COVID-19) disease affected people throughout the globe and has become a severe threat to the health and wellbeing of the global community. Time to death and predictors of mortality vary across settings. So far, no or few related studies have been undertaken in Ethiopia. Studying the time to death from COVID-19 and its predictors is essential to understand the characteristics of the disease and thereby contribute to the identification of indicators for early detection and initiation of treatment. Therefore, this study aimed to estimate time to death and its predictors among adults with COVID-19 in Ethiopia. Methods A retrospective follow-up study was conducted among 602 adults with COVID-19 attending Eka Kotebe General Hospital, COVID-19 Treatment Center, between 13 March 2020 and 13 November 2020. The data were entered by Epi-data version 4.2 while the analysis was carried out using STATA version 16. A Kaplan–Meier survivor curve was computed to estimate the survival probabilities. A log-rank test was used to compare the difference in survival curves. Cox proportional hazard models were fitted to identify the predictors of time to death. Results The overall median time to death was 21 days. Older adults (aged ≥65 years) [adjusted hazard ratio (AHR) 2.22, 95% confidence interval (CI) 1.02–4.86], being men (AHR 3.04, 95% CI 1.61–5.74), shortness of breathing at admission (AHR 2.29, 95% CI 1.16–4.54), comorbidity (AHR 2.23, 95% CI 1.04–4.80), diabetes mellitus (AHR 2.31, 95% CI 1.30–4.08), altered cardiac function (AHR 2.07, 95% CI 1.21–3.43), and baseline white blood cell count of greater than 10 (103/µl) (AHR 2.62, 95% CI 1.55–4.44) were independent predictors of COVID-19 mortality. Conclusion Male sex, older adults, shortness of breathing at admission, patients with comorbidities, and higher blood cell count were significant predictors of time to death from COVID-19. Therefore, concerned stakeholders should focus on those predictors of mortality and design interventions accordingly to enhance the survival of patients with COVID-19.