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To assess health-related quality of life (HRQoL), treatment satisfaction and associated factors among older adults with acute heart failure in Northwest Ethiopia.
Prospective, multicentre observational study.
Three tertiary hospitals in Northwest Ethiopia provide secondary and tertiary care services.
A total of 422 patients aged ≥60 years with a confirmed diagnosis of acute heart failure were consecutively enrolled between December 2024 and April 2025. Patients with unstable psychiatric conditions or advanced kidney disease were excluded.
HRQoL was assessed using the WHO Quality of Life – Brief Version questionnaire, and treatment satisfaction was measured using the Treatment Satisfaction Questionnaire for Medication (TSQM). Multiple linear regression identified factors associated with HRQoL and treatment satisfaction.
95% of participants reported moderate HRQoL, and 3% reported poor HRQoL. Weight loss was positively associated with HRQoL (β=1.52; 95% CI 0.04 to 3.07; p=0.021), whereas asthma was negatively associated with HRQoL (β = –3.28; 95% CI 6.94 to 0.37; p=0.001). Regarding treatment satisfaction, 65% of patients were moderately satisfied, with notable concerns regarding medication safety and overall experience. Rural residents reported lower satisfaction than urban residents (β = –0.20; 95% CI 0.34 to 0.05; p=0.007). Patients with New York Heart Association (NYHA) class III had higher satisfaction (β=0.25; 95% CI 0.05 to 0.45; p=0.016). Effective hypertension management was linked to increased satisfaction (β=0.20; 95% CI 0.02 to 0.37; p=0.026), whereas coronary heart disease was associated with lower satisfaction (β = –0.40; 95% CI 0.64 to 0.88; p=0.012).
Among older adults with heart failure in Northwest Ethiopia, 98% reported moderate to low HRQoL. Asthma and polypharmacy negatively affected HRQoL, whereas weight loss was positively associated with HRQoL. An NYHA class III status and well-managed hypertension improved treatment satisfaction, whereas rural residency and coronary heart disease were associated with lower satisfaction. These findings underscore the need for targeted interventions to enhance outcomes and QoL in this vulnerable population.
by Halid Worku Jemil, Sonia Worku Semayneh, Altaseb Beyene Kassaw, Kassahun Dessie Gashu
IntroductionSevere stunting is one of the primary public health challenges in LMIC including Eastern African Countries, which affects millions of children. In addition, it was a major contributor for mortality and related complication of children aged under five. However, there is limited study conducted severe form of stunting by employing Machine learning (ML) in Eastern African Countries. Therefore, our study was demonstrated to predict and identify its major determinants using ML algorithms, furthermore, to improve model explainablity. Our study used Shapley Additive explanations (SHAP) and ARM to identify the determinants of severe stunting among under-five.
Methodscross-sectional study was conducted using DHS data from 2012–2022 in East Africa. 136,074 children were the source populations, and 76,019 children were the study population. Data were analyzed using Python version 3.7 and R version 4.3.3 for data preprocessing, modeling, and statistical analysis. Model performance was evaluated using accuracy and AUC. Furthermore, the SHAP analysis and ARM was used to further explain and interpret the determinants of severe stunting among children under five.
ResultsThe Random Forest performed the best in this analysis, with an accuracy of 87% and an AUC score of 0.83. The analysis indicated that women’s who do not practicing exclusive breastfeeding (SHAP value = +0.41), being from Burundi (SHAP value = +0.04), children being underweight (SHAP value = +0.25), lived in poor household (SHAP value = +0.40), child gender being male(SHAP value = +0.23), mothers height being short (SHAP value = +0.03), mothers being underweight (SHAP value = +0.18), child size at birth being small (SHAP value = +0.21), women’s being delivered in home(SHAP value = +0.07), mothers education being primary (SHAP value = +0.20), unimproved toilet (SHAP value = +0.06), distance to health facility being a big problem (SHAP value = +0.02), were associated with increase the risk of severe stunting among under five.
ConclusionThe Random Forest was the best-performing model for predicting severe stunting in Eastern African countries. To decrease the effects of severe stunting, integrated interventions should provide support for mothers with lower socioeconomic conditions, strengthen maternal education, empower women to practice exclusive breastfeeding, encourage facility deliveries, increase access for households to sanitary facilities, provide education on personal and environmental hygiene, provide mothers with information on the importance of complementary feeding for children as well as for the mothers, and provide near health facilities for mothers and essential care services.
To ascertain the clinical impact, prevalence and associated determinants of delayed treatment intensification, defined as delaying the escalation of treatment plans for individuals with type 2 diabetes mellitus who fail to attain ideal glycaemic control, at the University of Gondar Comprehensive Specialised Hospital in Northwest Ethiopia.
A mixed-methods study.
University of Gondar Comprehensive Specialised Hospital.
420 patients with type 2 diabetes mellitus with poor glycaemic control after the index date were included in this study. A simple random sampling technique was employed to select the required sample size. Data were collected retrospectively and entered into EpiData V.4.6 and exported to Stata V.14.2 for analysis.
Multivariable logistic regression was used to identify factors associated with delayed treatment intensification. A p value of 0.05 in the multivariable analysis was considered statistically significant. Qualitative data were collected through in-depth interviews with eight selected healthcare providers, and thematic analysis was undertaken to identify the underlying barriers to timely treatment intensification.
Delayed treatment intensification.
The prevalence of delayed treatment intensification was 51.4% (95% CI 46.6% to 56.2%), with a median delay of 14 months (IQR: 7.5–42 months) from the index date. Among those experiencing delayed treatment intensification, 43.1% developed new chronic diabetic complications, including retinopathy (18.1%), neuropathy (14.4%) and nephropathy (6.0%). Other complications (hypertension, stroke, heart failure and diabetic foot ulcer) accounted for 4.64% of the cases. Significant predictors of delayed treatment intensification included longer duration of diabetes (adjusted ORs (AOR) 1.68; 95% CI 1.13 to 2.5), presence of comorbidities (AOR 1.83; 95% CI 1.04 to 3.2) and use of cardioprotective medications (AOR 1.59; 95% CI: 1.04 to 2.43). The qualitative findings revealed additional barriers contributing to delayed treatment intensification, including financial limitations, insufficient patient awareness and non-adherence among patients. Additionally, healthcare provider-related factors, including professional fatigue and knowledge gaps, as well as health institution-related factors such as inadequate healthcare infrastructure.
This study found a high prevalence of delayed treatment intensification (51.4%), associated with comorbidities, longer disease duration, low patient awareness, cardioprotective drug use and barriers related to the system and providers. To address these gaps, priorities should include strengthening patient education, scheduling regular reviews for high-risk patients and improving clinical decision support tools for timely treatment intensification. Enhancing healthcare infrastructure, such as medication supply and diagnostic services, and offering refresher training to reduce provider fatigue, are also crucial for improving the delivery of diabetes care.
Gestational trophoblastic disease, characterised by abnormal proliferation of trophoblastic tissue in the placenta during pregnancy, contributes to maternal morbidity and mortality. This study aimed to estimate the pooled prevalence and histopathological patterns of gestational trophoblastic disease in Africa, where previous studies have reported inconsistent findings.
Systematic review and meta-analysis adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 guidelines.
We searched PubMed, ScienceDirect, Hinari and Google Scholar for studies published between January 2000 and January 2024.
Institution-based observational studies from African countries reporting the prevalence and/or histopathological patterns of gestational trophoblastic disease, using total deliveries as the denominator.
Data were extracted into Excel and analysed using Stata V.17. Pooled estimates were calculated using a random-effects model with Knapp-Hartung adjustment. Heterogeneity was assessed with Cochran’s Q test and the I² statistic, and study quality was evaluated using the Joanna Briggs Institute tool.
Of the 2252 studies identified, 33 were included, comprising 2885 gestational trophoblastic disease cases from eight countries. The pooled prevalence of gestational trophoblastic disease in Africa was 4.35 per 1000 deliveries (95% CI 3.26 to 5.45, I2=99.8%). The pooled prevalence of hydatidiform mole, invasive mole and choriocarcinoma in Africa was 3.49 per 1000 deliveries (95% CI 2.45 to 4.52, I2=99.7%), 0.47 per 1000 deliveries (95% CI 0.14 to 0.79, I2=72.2%) and 0.97 per 1000 deliveries (95% CI 0.54 to 1.40, I2=99.1%), respectively.
This review indicated the prevalence of gestational trophoblastic disease was high. Hydatidiform mole was the predominant histopathological pattern observed. Routine antenatal screening is needed for early detection. Further research should be conducted to identify risk factors and evaluate strategies for the prevention and management of the disease.
CRD42024504268.
FreshRSS 