Sickle cell disease (SCD) is due to the mutation of haemoglobin (Hb), from HbA to HbS and characterised by recurrent vaso-occlusive crises (VOC), which can progress to acute chest syndrome (ACS), a leading cause of death in adults with SCD. Hypoxia is a key modifiable factor in the polymerisation of HbS and the pathogenesis of VOC. High-flow nasal oxygen (HFNO) delivers humidified gas at high oxygen concentrations and flow rates: the former may reverse sickling (metabolic effect) to accelerate VOC resolution and prevent ACS, while the latter may reduce the risk of ACS by mitigating hypercapnia and generating positive airway pressure that limits hypoventilation and atelectasis (pulmonary effect). The study hypothesises that HFNO is a safe and effective strategy for treating VOC and preventing secondary ACS, and will assess this using a multi-arm multi-stage (MAMS) trial design.

This is a prospective, multicentre, randomised, open-label controlled trial following an MAMS design with three phases and four arms: one control (low-flow oxygen) and three HFNO intervention arms with varying fraction of inspired oxygen levels (low, intermediate, high). The pilot stage will assess safety and feasibility, using the rate of cardiac and neurological events as the primary endpoint. In the activity stage, arms demonstrating acceptable safety will be compared for efficacy based on the rate of VOC resolution without complications by day 5, allowing selection of the most promising arm. The final efficacy stage will compare the selected HFNO strategy to control, with prevention of secondary ACS by day 14 as the primary endpoint. The study aims to enrol up to 350 VOC episodes in total.

The study has been granted ethical approval (CPP SUD MEDITERRANEE IV). Following the provision of informed consent, patients will be included in the study. The results will be submitted for publication in peer-reviewed journals.

NCT03976180.

This study employs structural equation modelling to explore the inter-relationships among optimal antenatal care (ANC), health facility delivery and early postnatal care (EPNC) in Ethiopia. By identifying both direct and indirect influencing factors, the study offers valuable insights to support integrated maternal health strategies and guide informed decision-making by policymakers and women alike.

The secondary analysis of the Ethiopian Demographic and Health Survey 2016 was performed to investigate inter-relationships between optimal ANC, health facility delivery and postnatal care (PNC) among women in Ethiopia. Data were analysed with R software V.4.3.2. The study used binary logistic regression to examine differences in optimal ANC, health facility delivery and EPNC, focusing on variables with a p value of 0.1 or less. Selected variables were incorporated into a generalised structural equation model (GSEM) using the LAVAAN package to explore both direct and indirect effects. The GSEM method assessed the impact of exogenous variables on endogenous variables, all binary, using a logistic link and binomial family. Missing data were handled with the multiple imputation by chained equations package, and sampling weights were applied to ensure national and regional representativeness.

The source population comprised all women of reproductive age (15–49 years) who gave birth in the 5 years preceding the survey. From 16 650 interviewed households (98% response rate), we identified 7590 eligible women with recent births. Finally, we included 2415 women who had attended four or more ANC visits.

Media exposure significantly boosts the likelihood of using ANC (OR=1.8, 95% CI (1.04 to 3.23), p=0.04), health facility delivery (OR=1.7, 95% CI (1.23 to 2.45), p=0.05) and PNC (OR=2.0, 95% CI (1.6 to 4.01), p=0.01). Urban residence and secondary education also enhance ANC (OR=1.2, 95% CI (1.01 to 2.88), p=0.022; OR=1.3, 95% CI (1.20 to 3.01), p=0.018), health facility delivery (OR=1.1, 95% CI (1.01 to 3.24), p=0.035; OR=1.5, 95% CI (1.22 to 3.45), p=0.03) and PNC (OR=1.6, 95% CI (1.01 to 4.32), p=0.03). ANC directly affects health facility delivery (OR=1.4, 95% CI (1.28 to 3.09), p=0.01) and PNC (OR=1.6, 95% CI (1.01 to 3.80), p=0.03). Additionally, women aged 20–34 years and those from male-headed households positively impact health facility delivery (OR=1.5, 95% CI (1.20 to 4.80), p=0.01; OR=1.3, 95% CI (1.07 to 3.45), p=0.014) and PNC (OR=1.4, 95% CI (1.10 to 2.90), p=0.01; OR=1.2, 95% CI (1.07 to 3.08), p=0.025).

Optimal ANC is vital for encouraging health facility delivery and EPNC. To enhance maternal and neonatal health, policies should integrate these services. Key predictors include being aged 20–34, having secondary and higher education, media exposure, male-headed households and living in urban areas. Improving education and media exposure can boost maternal healthcare service use.

To assess the incidence of delirium and its predictors among adult patients admitted to the intensive care units of comprehensive specialised hospitals in the Amhara region of northwest Ethiopia from 18 October 2024 to 20 February 2025.

A multicentre prospective observational study was conducted.

Four comprehensive specialised hospitals in the Amhara region of northwest Ethiopia, from 18 October 2024 to 20 February 2025.

A total of 351 patients were included in the final analysis during the study period.

The primary outcome measure of this study was the incidence of delirium. Additionally, the study investigated the factors associated with delirium incidence among adult patients admitted to intensive care units.

The incidence of delirium among adult patients in intensive care units was 42.17% (95% CI: 37.08 to 47.42). Pain (adjusted HR (AHR) = 4.74; 95% CI: 2.38 to 9.44), mechanical ventilation (AHR = 2.96; 95% CI: 1.56 to 5.63), age 65 years or older (AHR = 2.18; 95% CI: 1.48 to 3.21) and agitation (Richmond Agitation-Sedation Scale (RASS) ≥1) (AHR = 3.26; 95% CI: 2.09 to 5.09) were statistically significant factors associated with delirium.

In the present study, more than one-third of patients developed delirium. Pain, mechanical ventilation, age 65 or older and agitation (RASS≥1) were significantly associated with delirium occurrence. To reduce the incidence of delirium, the current study recommends treating or preventing pain and agitation. Additionally, special attention should be given to patients receiving mechanical ventilation and those aged 65 or older during care.

Ethiopia, the second most populous country in Africa, faces significant demographic transitions, with fertility rates playing a central role in shaping economic and healthcare policies. Family planning programmes face challenges due to funding limitations. The recent suspension of the US Agency for International Development funding exacerbates these issues, highlighting the need for accurate birth forecasting to guide policy and resource allocation. This study applied time-series and advanced machine-learning models to forecast future birth trends in Ethiopia.

Secondary data from the Ethiopian Demographic and Health Survey from 2000 to 2019 were used. After data preprocessing steps, including data conversion, filtering, aggregation and transformation, stationarity was checked using the Augmented Dickey-Fuller (ADF) test. Time-series decomposition was then performed, followed by time-series splitting. Seven forecasting models, including Autoregressive Integrated Moving Average, Prophet, Generalised Linear Models with Elastic Net Regularisation (GLMNET), Random Forest and Prophet-XGBoost, were built and compared. The models’ performance was evaluated using key metrics such as root mean square error (RMSE), mean absolute error (MAE) and R-squared value.

GLMNET emerged as the best model, explaining 77% of the variance with an RMSE of 119.01. Prophet-XGBoost performed reasonably well but struggled to capture the full complexity of the data, with a lower R-squared value of 0.32 and an RMSE of 146.87. Forecasts were made for both average monthly births and average births per woman over a 10-year horizon (2025–2034). The forecast for average monthly births indicated a gradual decline over the projection period. Meanwhile, the average births per woman showed an increasing trend but fluctuated over time, influenced by demographic shifts such as changes in fertility preferences, age structure and migration patterns.

This study demonstrates the effectiveness of combining time-series models and machine learning, with GLMNET and Prophet XGBoost emerging as the most effective. While average monthly births are expected to decline due to demographic transitions and migration, the average births per woman will remain high, reflecting persistent fertility preferences within certain subpopulations. These findings underscore the need for policies addressing both population trends and sociocultural factors.

To assess the incidence, progression and predictors of chronic kidney disease among adult patients living with HIV/AIDS who are receiving antiretroviral therapy.

An institution-based, multicentre retrospective follow-up study was conducted among a randomly selected sample of 535 adult patients. Data were entered into Epi Data version 4.6.0 and analysed using STATA version 14.0. A Cox proportional hazards regression model was fitted to identify independent predictors of chronic kidney disease incidence. Variables with p

The study was conducted at comprehensive specialised hospitals in the Amhara Region of Ethiopia. Adult patients with HIV/AIDS receiving follow-up antiretroviral therapy between 1 April 2012 and 31 September 2022 were the cohort participants.

Of the 528 adult patients included in the final analysis, 15 (2.84%) developed chronic kidney disease during the follow-up period, resulting in an overall incidence rate of 4.1 per 1000 person-years of observation. Significant predictors of chronic kidney disease included baseline age (adjusted HR (AHR)=1.053; 95% CI, 1.001 to 1.108), serum creatinine (AHR=1.698; 95% CI, 1.302 to 2.215), blood urea nitrogen (AHR=1.031; 95% CI, 1.001 to 1.061) and baseline viral load ≥1000 copies/mL (AHR=3.464; 95% CI, 1.104 to 10.871).

The incidence of chronic kidney disease among adult patients with HIV was clinically significant. Older age, baseline viral load ≥1000 and high blood urea nitrogen and creatinine levels were significant predictors of higher risk. Proactive measures, such as closer kidney monitoring, targeted care for older patients and ensuring optimal viral suppression with effective antiretroviral therapy, can delay or prevent the development of chronic kidney disease.

Non-adherence to antidiabetic medication remains a major barrier to achieve optimal health outcomes among individuals with diabetes, particularly in developing countries. This issue exacerbates poor health outcomes and leads to the wastage of limited healthcare resources.

This study aimed to assess the prevalence of non-adherence to antidiabetic medications and identify associated factors among adult type 2 diabetes mellitus (DM) patients in the North Wollo zone.

An institutional-based cross-sectional study.

The study was conducted in three randomly selected public hospitals in the North Wollo zone: Woldia Comprehensive Specialized Hospital, Lalibela General Hospital and Mersa Primary Hospital.

A total of 327 adult type 2 DM patients receiving follow-up care were included. Participants were selected proportionally from each hospital using consecutive sampling. Inclusion criteria included individuals aged ≥18 years, on antidiabetic treatment for at least 6 months and actively on follow-up care during the study period. Patients with hearing impairment, severe illness or incomplete medical records were excluded.

Adherence was assessed using the Morisky Medication Adherence Scale-8, a validated eight-item, self-reported questionnaire. Scores ranged from 0 to 8, with adherence levels classified as high (≥8), medium (6–7.75) and low (

Data were analysed using SPSS V.27. Descriptive statistics were used to summarise the data, and multivariable logistic regression analysis was performed to identify factors associated with non-adherence. A p value ≤0.05 was considered statistically significant.

The overall prevalence of medication non-adherence was 24.5%. Factors significantly associated with non-adherence included living with diabetes for less than 3 years (adjusted OR (AOR) 3.37, 95% CI 1.91 to 5.95), residing in rural areas (AOR 2.67, 95% CI 1.49 to 4.79), having comorbidities (AOR 2.99, 95% CI 1.67 to 5.34) and having no formal education (AOR 3.26, 95% CI 1.49 to 7.00).

The prevalence of non-adherence to antidiabetic medications (24.5%) exceeded the widely accepted benchmark of ≤20%. Key factors such as rural residence, comorbidities, lower education levels and shorter duration since diagnosis were significantly associated with non-adherence. These findings underscore the need for targeted interventions, including patient education, improved rural healthcare access and integrated care models, to enhance adherence and diabetes management outcomes.