Competing Risk Survival analysis of time to in-hospital mortality or Recovery among Covid-19 Patients in South-East Ethiopia: a hospital-based multisite study

Background: To date, survival data on risk factors for COVID-19 mortality in south-Ethiopia is limited, and none of the published survival studies have used a competing risk approach. This study aims to identify risk factors for in-hospital mortality in COVID-19 patients hospitalized at one of the six hospitals in southeast-Ethiopia, considering recovery as a competing risk. Methods: This observational multisite study included a medical record of 827 confirmed SARS-CoV-2 cases hospitalized at one of the six hospitals in southeast-Ethiopia from October 1, 2022 to May 31, 2023. We compiled data on the patients' socio-demographic characteristics, clinical manifestation, comorbidity, treatment status, treatment outcomes, and length of stay. We performed a Cox regression analysis for competing risks, presenting cause-specific hazard ratios (HRcs) for the effect of preselected factors on the absolute risk of death and recovery. Results: 827 patients were included (51.9% male; median age 50 years, IQR: 38-65). Patients were hospitalized for a median duration of 5 days (IQR: 1-7); 139 (17%) of them died, while 516 (62%) were recovered and discharged alive, the rest 172 (21%) were censored. Patients with higher age (HRcs 2.62, 95% CI 1.29-5.29), immune-compromised state (HRcs 1.46, 95% CI 1.08-1.98) had increased risk of death, whereas male sex paradoxically (HRcs 0.45, 95% CI 0.22-0.91) associated with decreased risk of death. We found no increased mortality risk in diabetes patients. Conclusion: This competing risk survival analysis allows us to corroborate specific pattern of risk factors about COVID-19 mortality and its progression among different groups of individuals (differentiated by age and immune-compromised state). 62% presenting cases recovered within a median duration of 5 days; where as 17% die within the first 72 hours, most with immune-compromised conditions. This should be considered while planning and allocating the distribution of care services for effective health service delivery.