Conectar
In sub-Saharan African countries, the population-based assisted vaginal birth (AVB) rate is approximately 1% as compared with 16% in Western Europe. Consequently, women experiencing prolonged labour often face limited access to prompt intervention, leading to maternal and perinatal complications or unnecessary caesarean sections (CS). The OdonAssist device has been developed to be safe, user-friendly and more acceptable than currently used AVB devices. We propose to conduct a study in Ethiopia to evaluate if the implementation of this innovation is feasible and may contribute to improving the access to AVB while reducing unnecessary CSs.
We designed a single-centre feasibility study at Saint Luke Catholic Hospital (Wolisso, Ethiopia), a secondary facility where AVB is routinely performed by midwives and health officers under gynaecologist supervision, reflecting the local health system. Following a quasi-experimental design, we will include three groups of 20 women: an intervention group (OdonAssist), a vacuum extraction cohort and a control group of second-stage CS (performed without a prior trial of instrumental birth). The primary objective is to assess the clinical and methodological feasibility of the OdonAssist by collecting preliminary data on safety, acceptability and quantifying potential efficacy relative to the current standard of care. An exploratory economic evaluation of direct healthcare costs will be performed.
Approved by the Oromia Regional Health Bureau. The study results will be published in peer-reviewed journals to inform future impact evaluations of the OdonAssist device in global maternal and perinatal health.
by Boru Abera Ebsa, Maleda Tefera, Dawit Tamiru, Abraham Negash, Naol Oda, Merga Dheresa
BackgroundThe neonatal period is the most vulnerable time for an infant’s survival, particularly for preterm neonates. Preterm birth is among the leading causes of neonatal mortality. Many neonatal complications can be prevented, but preterm birth remains a leading cause of admission, death, and long-term complications, highlighting the need for further research on outcome and survival disparities across populations and settings. Therefore, this study aimed to assess survival status and predictors of mortality among preterm neonates admitted to neonatal intensive care units at public hospitals in the Harari region and Dire Dawa administration, Eastern Ethiopia, from November 1, 2021 to October 30, 2024.
MethodsThe hospital-based retrospective cohort study was conducted among preterm neonates admitted to the neonatal intensive care unit at public hospitals of the Harari region and Dire Dawa administration, Eastern Ethiopia. A simple random sampling technique was used, and data were extracted from neonates’ medical records and registration formats using a structured checklist prepared in English. Descriptive statistics, life table, Kaplan-Meier curves, and Log-rank test were used to estimate and compare survival time. Predictors of mortality were identified using the Cox Proportional Hazard model.
ResultsOut of 612 preterm neonates, 205 (33.5%; 95% CI: 29.76–37.39) died, corresponding to an incidence rate of 52.76 deaths per 1,000 preterm neonate-days (95% CI: 46.01–60.50), with a median survival time of 18 days. As multivariable cox-regression result, ≥ 4 antenatal care contact (AHR = 0.56; 95% CI: 0.36–0.89), receiving KMC (AHR = 0.16; 95% CI: 0.09–0.27), 5th minute APGAR score Conclusion
The incidence of preterm neonatal mortality was high in this study. Adequate Antenatal care (ANC) and kangaroo mother care (KMC) significantly improved preterm survival, while low APGAR score, resuscitation with bag and mask, neonatal sepsis, PNA, and RDS were major predictors of preterm neonatal death. Emphasis should be placed on strengthening antenatal and perinatal care, along with early detection and management of identified neonatal complications.
by Merga Abdissa Aga
We propose the Fréchet–Power Function (FPF) distribution, a novel two-parameter model that combines the bounded support of the Power Function distribution with the heavy-tailed flexibility of a Fréchet-type generator. This combination enables the FPF to capture complex features such as skewness, heavy tails, and diverse hazard rate shapes—limitations present in existing bounded lifetime models. We provide explicit forms for the probability density, cumulative distribution, and quantile functions, along with detailed statistical properties including moments and hazard rate behavior. Parameters are estimated using maximum likelihood, with bootstrap and simulation techniques employed to assess estimator performance. Empirical applications to survival, reliability, and environmental datasets show that the FPF distribution consistently outperforms traditional models in terms of goodness-of-fit and flexibility. This work introduces a powerful and versatile tool for modeling bounded lifetime data, offering enhanced accuracy and interpretability across disciplines.
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