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

BackgroundTo 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. MethodsThis 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. Results827 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. ConclusionThis 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