Predictors, causes, and trends of neonatal mortality at Nekemte Referral Hospital, east Wollega Zone, western Ethiopia (2010-2014). Retrospective cohort study.

BackgroundNeonatal mortality is a significant contributor to infant mortality. Causes and predictors of neonatal death are known to vary in different settings and across different contexts. This study aimed to assess predictors, causes, and trends of neonatal mortality amongst neonates admitted to Nekemte Referral Hospital neonatal unit between 2010-2014.MethodsRetrospective data was collected for 2090 live born neonates admitted to the neonatal intensive care unit of Nekemte Referral Hospital by reviewing records between 2010 to 2014. Variables were collected from the neonatal registration book and patient card on the predictors, causes, and trends of neonatal death using a standard checklist developed by the World Health Organization (WHO). Data was analyzed using Epi info version 3.5.1, and SPSS version 25 for windows. The level of significance was set at PResultsThere were 183 deaths in the cohort equivalent to 8.8% of deaths among total admitted neonates during the study period. Early neonatal deaths accounted for 8% and late neonatal deaths accounted for 0.71% of deaths among total admitted neonates. Main predictors identified for an increased risk of neonatal mortality were; neonates from rural residents [AOR 1.35, (95% CI, 1.35-1.87)], birth order of greater than five [AOR 5.10, (95% CI, 1.15-22.63)], home delivery [AOR 3.41, (95% CI, 2.24-5.19)], very low birth weight [AOR 6.75, (95% CI, 3.63-12.54)] and low birth weight [AOR 2.81, (95% CI, 1.95-4.05)] and inability to cry at birth [AOR 2.21, (95% CI, 1.51-3.22)]. The trend analysis showed a sharp fall for the neonatal mortality over the last five years with a mean reduction of 16%.ConclusionsData from the Nekemte Referral Hospital Neonatal Intensive Care Unit analysis revealed majority of the deaths were occurred during early neonatal period. The main predictors of neonatal mortality identified from this study needs strengthening an appropriate public health intervention through addressing antenatal care, curbing home delivery

Time to recovery from COVID-19 and its predictors among patients admitted to treatment center of Wollega University Referral Hospital (WURH), Western Ethiopia: Survival analysis of retrospective cohort study.

IntroductionDespite its alarming spread throughout the world, no effective drug and vaccine is discovered for COVID-19 so far. According to WHO, the recovery time from COVID-19 was estimated to be 2 weeks for patients with mild infection, and 3 to 6 weeks for those with serious illnesses. A studies regarding the median recovery time and its predictors are limited globally and specifically in Ethiopia. Therefore, the aim of this study was to estimate the median time to recovery from COVID-19 and its predictors among COVID-19 cases admitted to WURH, Western Ethiopian.MethodsThis was a hospital-based retrospective cohort study conducted among 263 adult patients admitted with COVID-19 in WURH treatment center from March 29, 2020 through September 30, 2020. Epidata version 3.2 was used for data entry, and STATA version 14 for analysis. A Cox proportional hazard regression model was fitted to determine factors associated with recovery time. A variable with P-value ≤ 0.25 at bivariable Cox regression analysis were selected for multivariable Cox proportional model. Multivariable Cox regression model with 95% CI and Adjusted Hazard Ratio (AHR) was used to identify a significant predictor of time to recovery from COVID-19 at P-value ResultsThe mean age of patient was 36.8 (SD± 10.68) years. At the end of follow up, two hundred twenty seven observations were developed an event (recovered) with median time to recovery of 18 days with IQR of 10-27 days. The overall incidence rate of recovery was of 4.38 per 100 (95% CI: 3.84, 4.99) person-days observations. Being older age (AHR = 1.59, 95% CI: 1.02, 2.49), presence of fever on admission (AHR = 1.78, 95% CI: 1.21, 2.62), and comorbidity (AHR = 0.56, 95% CI, 0.34, 0.90) were found to have statistically significant association with recovery time.Conclusion and recommendationsIn general, the median recovery time of patients with COVID-19 cases was long, and factors such as older age group, presence of fever, and comorbidity was an independent predictors of delayed recovery from COVID-19. Intervention to further reduce recovery time at treatment center has to focus on patients those shows symptoms and with comorbidities