ObjectiveTo determine the incidence and predictors of mortality among children admitted to the paediatric intensive care unit (PICU) at the University of Gondar comprehensive specialised hospital, northwest Ethiopia.DesignA single-centre prospective observational cohort study.ParticipantsA total of 313 children admitted to the ICU of the University of Gondar comprehensive specialised hospital during a one-and-a-half-year period.MeasurementsData were collected using standard case record form, physical examination and patient document review. Clinical characteristics such as systolic blood pressure, pupillary light reflex, oxygen saturation and need for mechanical ventilation (MV) were assessed and documented within the first hour of admission and entered into an electronic application to calculate the modified Pediatric Index of Mortality 2 (PIM 2) Score. We fitted the Cox proportional hazards model to identify predictors of mortality.ResultThe median age at admission was 48 months with IQR: 12–122, 28.1% were infants and adolescents accounted for 21.4%. Of the total patients studied, 59.7% were males. The median observation time was 3 days with (IQR: 1–6). One hundred and two (32.6%) children died during the follow-up time, and the incidence of mortality was 6.9 deaths per 100 person-day observation. Weekend admission (adjusted HR (AHR)=1.63, 95% CI: 1.02 to 2.62), critical illness diagnoses (AHR=1.79, 95% CI: 1.13 to 2.85), need for MV (AHR=2.36, 95% CI: 1.39 to 4.01) and modified PIM 2 Score (AHR=1.53, 95% CI: 1.36 to 1.72) were the predictors of mortality.ConclusionThe rate of mortality in the PICU was high, admission over weekends, need for MV, critical illness diagnoses and higher PIM 2 scores were significant and independent predictors of mortality.

Introduction The Bacille-Calmette–Guerin (BCG) vaccination remains the primary strategy to prevent severe disseminated TB in young children, particularly in high TB-burden countries such as Ethiopia. Accurate knowledge of vaccination coverage in small geographical areas is critically important to developing targeted immunization campaigns. Thus, this study aimed to investigate the spatiotemporal distributions and ecological level determinants of BCG vaccination coverage in Ethiopia. Method Bacille-Calmette–Guerin immunization coverage and geographical information data were obtained from five different Demographic and Health Surveys, conducted in Ethiopia between 2000 and 2019. Data for independent variables were obtained from publicly available sources. Bayesian geostatistical models were used to predict the spatial distribution of BCG vaccination coverage in Ethiopia. Result The overall national BCG vaccination coverage between 2000 and 2019 was 65.5%. The BCG vaccine coverage was 53.5% in 2000, 56.9% in 2005, 64.4% in 2011, 79.6% in 2016, and 79.0% in 2019. BCG vaccination coverage increased by 47.6% in Ethiopia from 2000 to 2019, but substantial geographical inequalities in BCG coverage remained at sub-national and local levels. High vaccination coverage was observed in northern, western, and central parts of Ethiopia. Climatic and demographic factors such as temperature, altitude, and population density were positively associated with BCG vaccination coverage. Whereas, healthcare access factors such as distance to health facilities and travel time to the nearest cities were negatively associated with BCG vaccine coverage in Ethiopia. Conclusion Despite substantial progress in national BCG vaccination coverage, marked spatial variation in BCG coverage persists throughout the country at sub-national and local levels. Healthcare access and climatic and demographic factors determined the spatial distribution of BCG vaccination coverage. Maintaining a high level of vaccination coverage across geographical areas is important to prevent TB in Ethiopia.

BackgroundDespite progress in reducing maternal and child mortality, many low- and middle-income countries (LMICs) still experience an unacceptably high level of the problem. The World Health Organization (WHO) recently recommended pregnant women should have at least eight antenatal care visits (ANC8+) with a trained healthcare provider as a key strategy to promote pregnant women's health. Antenatal care is an imperative factor for subsequent maternal healthcare utilization such as health facility delivery and early postnatal care (EPNC). This study aimed to examine the net impact of ANC8+ visits on health facility delivery and EPNC in LMICs using a propensity score matching analysis.MethodsWe used the recent Demographic and Health Survey (DHS) datasets from 19 LMICs. Women of reproductive age (15–49 years) who had given birth within 1 year preceding the survey were included. A propensity score matching analysis was employed to assess the net impact of eight or more antenatal care visits on health facility delivery and early postnatal care.ResultAfter matching the covariates, women who attended ANC8+ visits had a 14% (ATT = 0.14) higher chance of having their delivery at health facilities compared with women who attended less than eight ANC visits. This study further revealed that women who had ANC8+ visits were associated with a 10% (ATT = 0.10) higher probability of early PNC compared with their counterparts.Conclusion and recommendationThis study confirmed that ANC8+ visits significantly increased the likelihood of health facility-based delivery and early PNC utilization in LMICs. These findings call for public health programs to focus on pregnant women attending adequate ANC visits (according to revised WHO recommendation) as our study indicates that ANC8+ visits significantly improved the chances of subsequent care.

Background Pediatric intensive care unit (PICU) tremendously improves the success of saving patients having potentially life-threatening illness. An accurate estimate of lives saved through pediatric critical care intervention is important to evaluate the quality of the health care system. Data on pediatric critical care in developing countries remain scarce yet is much needed to improve clinical practices and outcomes. This study aimed to determine the incidence and predictors of mortality in the pediatric intensive care unit in the study setting.Method An institution based prospective cohort study was conducted from February 2018 to July 2019. We collected data by interview, chart and registration book review. Life table was used to estimate the cumulative survival of patients and Log rank test was used to compare survival curves between different categories of the explanatory variables. Survival trend over the follow up time was described using the Kaplan Meier graph. Bivariate and multivariate Cox proportional hazard model were used to identify predictors.Result Based on the 10 th version of international classifications of disease (ICD) of WHO, neurologic disorders (22.7%) infectious disease (18.8%) and environmental hazards (11.8%) account for the top three diagnoses. The median observation time was 3 days with IQR of 1 to 6 days. Of the total of 313 participants, 102 (32.6%) died during the follow-up time. This gives the incidence of mortality of 6.9 deaths per 100 person day observation. Caregivers’ occupation of government-employed (AHR=0.35, 95%CI: 0.14, 0.89), weekend admission (AHR=1.63, 95%CI: 1.02, 2.62), critical illness (AHR=1.79, 95%CI: 1.13, 2.85) Mechanical ventilation AHR=2.36,95%CI: 1.39, 4.01)and PIM2 score (AHR=1.53, 95%CI: 1.36, 1.72) were predictors of mortality in the pediatric ICU.Conclusion Neurologic disorder was the leading causes of admission followed by infectious diseases, and environmental hazards. Rate of mortality was high and admission over weekends, caregivers' occupation, mechanical ventilation, critical illness diagnosis, and higher PIM2 scores were found to be significant and independent predictors of mortality at the PICU. This suggests that ICU medical equipment, diagnostics, and interventions should be available up to the standard. Intensivist and full staffing around the clock has to be available in the PICU.

Background Nutritional problems are increasingly associated with acute infections. It is also related to further complications of illnesses and poor treatment outcomes of medical conditions. This study aimed to assess wasting and associated factors among critically ill children admitted to intensive care units at the time of admission. Methods An institution-based prospective observational study was employed among children admitted to pediatric intensive care of the University of Gondar Comprehensive Specialized Hospital from February 1, 2018, to July 30, 2019. Data about socio-demographic, clinical, and anthropometric measurements were taken from children at the time of admission and length of hospital stay and treatment-related data were collected by chart review at discharge. Summary measures were computed and presented in the form of text, tables, and graphs. A p-value of less than 0.2 was used to select candidate variables for multivariable analysis. A binary logistic regression model was fitted to identify factors associated with wasting. Adjusted odds ratio with 95% confidence interval (CI) was calculated and variables with a p-value less than 0.05 in the multi-variable analysis were considered to declare factors associated with wasting. Results The median age at admission was 48 (IQR: 12 to 122) months. Of the total admitted children to ICU, 47.97% were undernourished, of which 32% (95%CI: (26.8% to 37.4%) were severely wasted. Caregivers who had no formal education (AOR=4.43, 95%CI 1.62 12.10), transferred from wards (AOR=2.98, 95%CI: 1.02 8.69), duration of illness ≥6 days before health facility visit (AOR=2.14, 95%CI: 1.22 3.72) and comorbidity (AOR=6.85, 95%CI: 2.93 16.05) were statistically significant factors associated with wasting. Conclusion Wasting was high among children admitted to the intensive care unit. No formal education, transferred from wards and operation rooms, longer duration of illness before health facility visits, and comorbidity were factors associated with wasting. Wasted patients had higher mortality as compared to patients with no wasting. A multicenter study with larger sample size is recommended for a more generalizable result.