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BackgroundThe Corona virus disease 19 (COVID-19) pandemic is a human tragedy that occurred in this era. It poses an unprecedented psychological, social, economic, and health crisis. The mental health and well-being of entire societies are suffering as a result of this crisis, but the suffering is greater in students at all levels of education and must be addressed immediately. Thus, this study was aimed to estimate the pooled prevalence and associated factors of the psychological impact of COVID-19 among higher education students.MethodsThe potential studies were searched via PubMed, HINARI, the Cochrane Library, and Google Scholar. Studies were appraised using the Joanna Briggs Institute appraisal checklist. Micro Soft Excel was used to extract the data, which was then exported to Stata version 14 for analysis. Heterogeneity between studies was tested using Cochrane statistics and the I2 test, and small-study effects were checked using Egger’s statistical test. A random-effects model was employed to estimate the pooled prevalence of the psychological impact of COVID-19 and its associated factor.ResultsAfter reviewing 227 studies, eight fulfilled the inclusion criteria and were included in the meta-analysis. The pooled prevalence of the psychological impact of Corona virus disease 19 among higher education students in Ethiopia, including depression, anxiety, and stress was 43.49% (95% CI: 29.59, 57.40%), 46.27% (95% CI: 32.77, 59.78%), and 31.43% (95% CI: 22.71, 40.15), respectively. Having a medical illness, being an urban resident, living with parents, having relative death due to pandemics, and having a non-health field of study were identified as significant associated factors for the impact of the pandemic in higher education students.ConclusionThe COVID-19 pandemic had a significant psychological impact on college and university students. Depression, anxiety, and stress were the most commonly reported psychological impacts across studies among higher education students. Hence, applying tele-psychotherapy using, smartphones, and social media platforms has an effect on reducing the impact. Programs for preventing and controlling epidemics should be developed by the government and higher education institutions that incorporate mental health interventions and build resilience.

Background and Aims Utilizing health facility delivery services is one of the pillars of lowering maternal mortality. However, the coverage of health facility delivery service utilization continues to be uneven around the world. In Ethiopia, particularly among pastoralist regions, health facility delivery service utilization is less common. Therefore, the purpose of this study was to determine the pooled prevalence of health facility delivery service utilization and identify the associated factors among women in the pastoralist regions of Ethiopia. Methods A comprehensive systematic search was carried out in PubMed/MEDLINE, Hinary, Cochrane Library, Google Scholar, Google, and Ethiopian online university repositories. Studies were appraised using the JBI appraisal checklist. The analysis was done using STATA version 16. The pooled analysis was conducted using DerSimonian and Laird random‐effects model. I 2 test and Eggers & Begg's tests were used to assess the heterogeneity and publication bias, respectively. p < 0.05 was set to determine the statistical significance of all the tests. Results The pooled prevalence of health facility delivery service utilization was 23.09% (95% CI: 18.05%−28.12%). Have ANC visit during pregnancy (OR = 3.75, [95% CI: 1.84−7.63]), have information regarding maternal health service fee exemption (OR = 9.51, [95% CI: 1.41−64.26]), have a nearby health facility (OR = 3.49, [95% CI: 1.48−8.20]), and women attend secondary and above education (OR = 3.06, [95% CI: 1.77−5.29]) were found to be significant associated factors. Conclusions Health facility delivery service utilization is very low in pastoralist regions of Ethiopia, and ANC follow‐up, distance from the health facility, women's educational status, and information regarding maternal health service fees were identified as significant associated factors. Consequently, strengthening ANC services, introducing free health services to the community, and constructing health facilities for the nearby residents are recommended to improve the practice.

ObjectiveTo develop and validate a clinical risk score for in-hospital stroke mortality.DesignThe study used a retrospective cohort study design.SettingThe study was carried out in a tertiary hospital in the Northwest Ethiopian region.ParticipantsThe study included 912 patients who had a stroke admitted to a tertiary hospital between 11 September 2018 and 7 March 2021.Main outcome measuresClinical risk score for in-hospital stroke mortality.MethodsWe used EpiData V.3.1 and R V.4.0.4 for data entry and analysis, respectively. Predictors of mortality were identified by multivariable logistic regression. A bootstrapping technique was performed to internally validate the model. Simplified risk scores were established from the beta coefficients of predictors of the final reduced model. Model performance was evaluated using the area under the receiver operating characteristic curve and calibration plot.ResultsFrom the total stroke cases, 132 (14.5%) patients died during the hospital stay. We developed a risk prediction model from eight prognostic determinants (age, sex, type of stroke, diabetes mellitus, temperature, Glasgow Coma Scale, pneumonia and creatinine). The area under the curve (AUC) of the model was 0.895 (95% CI: 0.859–0.932) for the original model and was the same for the bootstrapped model. The AUC of the simplified risk score model was 0.893 (95% CI: 0.856–0.929) with a calibration test p value of 0.225.ConclusionsThe prediction model was developed from eight easy-to-collect predictors. The model has excellent discrimination and calibration performance, similar to that of the risk score model. It is simple, easily remembered, and helps clinicians identify the risk of patients and manage it properly. Prospective studies in different healthcare settings are required to externally validate our risk score.

Introduction Ventilator-associated pneumonia refers to pneumonia that happens at least 48 hours after endotracheal intubation. It is associated with high economic costs, longer attributable lengths of stay in the hospital, and high mortality. Therefore, this study aims to determine the incidence and predictors of ventilator-associated pneumonia among adult intensive care unit admitted patients at Bahir Dar Specialized Hospitals. Methods A retrospective follow-up study was conducted among 312 adult intensive care unit admitted patients. A data extraction checklist was used to collect the data. The collected data were coded, cleaned, and entered into EpiData version 3.1 and exported to SPSS version 22 and STATA version 14 for analysis. Descriptive analysis was done by using tables, text and percentages. Bivariable and multivariable log binomial analyses were conducted to identify predictors of ventilator-associated pneumonia. Variables having p-value <0.05 were considered statistically significant. Results The study found that 27.9% (95% CI: 23%–33%) of patients developed ventilator-associated pneumonia and the incidence rate of VAP was 45.7 per 1000 ventilator days. Patient's stay more than or equal to 14 days (ARR: 13, 95% CI: 9.3–31) and 7–13 days on MV (ARR: 7.2, 95% CI: 6.2–11), blood transfusion (ARR: 2.8, 95% CI: 1.1–6.9), low GCS (ARR: 2.5, 95% CI: 1.3–5.1), use of corticosteroid (ARR: 2.1, 95% CI: 1.1–4.1), and supine head position (ARR: 8.1, 95% CI: 1.7–40) were identified as independent predictors of ventilator associated pneumonia. Conclusion Nearly one-fourth of the participants developed ventilator-associated pneumonia. Duration of ventilation, blood transfusion, corticosteroid use, supine head position, and low Glasgow coma scale were significant predictors of ventilator-associated pneumonia.