Search

Abstract Introduction Acute coronary syndrome (ACS) accounts for coronary artery disease (CAD) –related morbidity and mortality. There has been growing concern about the rising incidence of ACS among young individuals globally both in developed and developing countries, including Sub-Saharan Africa. This group’s phenotypic characteristics; risk factors and clinical outcomes are not well described. contextual and regional studies are necessary to understand the magnitude of ACS among young Individuals and help highlight challenges and opportunities for improved ACS outcomes in the region. The study aimed to describe the demographic and clinical characteristics of young individuals hospitalized with ACS and report on in-hospital outcomes. Methodology This single-center retrospective study was conducted at the Aga Khan University Hospital, Nairobi. Medical records of all young individuals hospitalized with ACS from 30th June 2020 to 1st May 2023 were reviewed. We defined young individuals as 50 years or below. Categorical variables were reported as frequencies and proportions, and compared with Pearson chi- square or Fisher’s exact tests. Continuous variables were reported as means or medians and compared with independent t-tests or Mann-Whitney U tests. P- value

Background: Efficacy of Implantable Cardioverter-Defibrillator (ICD) implantation in both primary and secondary prevention of Sudden Cardiac Death (SCD) in at-risk population is well established. ICD implantation rates remain low particularly in Africa with a paucity of data regarding factors associated with non-uptake. Objectives: The primary study objective was to determine the factors associated with non-uptake of ICD among heart failure (HF) patients with reduced ejection fraction (EF

BACKGROUND: Severe maternal morbidity has been shown to have specific, long-term effects on health and wellbeing, such as daily functioning and mental health. OBJECTIVE: This study aimed to multidimensionally assess the long-term impact of maternal near-miss complications in Zanzibar. STUDY DESIGN: A prospective cohort study was conducted in Zanzibar's referral hospital. Women with maternal near-miss complications were matched with controls. At 3, 6, and 12 months after hospital discharge, history was taken, blood pressure and haemoglobin levels were measured, and multiple validated questionnaires (WHOQOL-BREF, WHODAS2.0, Patient Health Questionnaire-9, Harvard Trauma Questionnaire-16) were administered assessing experienced quality of life and disability, and screening for depression and posttraumatic stress disorder. RESULTS: We included 223 women after maternal near-miss complications and 213 women controls. There was a high prevalence of hypertension at 6 and 12 months in both groups and significantly higher after a near-miss. The proportion of women with low quality of life, disability, depression, or posttraumatic stress disorder was not significantly different between the 2 groups. A poor outcome for at least 1 of these 3 health domains was more prevalent after a near-miss complication. CONCLUSION: In Zanzibar, women after maternal near-miss complications report similar but slower recovery to control participants in the assessed dimensions. Adaptation of perceptions on and coping mechanisms with daily reality might partly explain this. Hypertension has a high prevalence after childbirth and should be treated adequately to prevent recurrent obstetrical and cardiovascular complications. Blood pressure follow-up for all women who delivered at Mnazi Mmoja Hospital seemed justified.

There appears to be an epidemiological transition in the etiology of heart failure in sub-Saharan Africa (SSA) in parallel with a steady increase in risk factors for coronary artery disease (CAD). SSA has limited access to heart failure and CAD diagnostics, limiting the number of patients who receive optimal care. Our objectives were to study the predictors of coronary artery disease among patients with heart failure with reduced ejection fraction (HFrEF) and develop a model to assist clinicians in determining the likelihood of CAD before cardiac catheterization. Methodology: This was a retrospective study at the Aga Khan University Hospital, Nairobi, which is equipped with diagnostic capabilities for heart failure and coronary artery assessment. We evaluated patients with HFrEF based on echocardiographic data over a 12-year period. Patients with coronary anatomical evaluation data were included. A multivariable model of CAD was generated using stepwise logistic regression. Results: Of the 1329 patients screened, 514 met the inclusion criteria. The mean age was 61.0 ± 12.8 years. There were 381 male cases (75.2%), and the predominant race was African, numbering 386 (75.2%). Most patients, 97%, were evaluated through conventional coronary angiography. Further, 310 (60.3%) cases had significant CAD. The prevalence of CAD in HFrEF was 52.3% in Africans, 85% in Asians, and 79% in Caucasians. In the multivariable logistic regression, the odds of having significant CAD was higher among participants with diabetes mellitus (aOR: 1.86; 95%CI: 1.15–3.03), Q waves (aOR: 2.12; 95%CI: 1.12–4.10), significant ST segment deviation (aOR: 4.14; 95%CI: 2.23–8.03), and regional wall motion abnormalities on echocardiogram (aOR: 6.53; 95%CI: 3.94–11.06). Conclusion: In this population, CAD was a major etiology in HFrEF among the African population. The most powerful predictors of CAD were type 2 diabetes, the presence of pathological Q waves, or ST segment shift on a 12-lead electrocardiogram, and regional wall motion abnormality on 2D echocardiogram. Highlights • There is an epidemiological transition in the cause of heart failure in sub-Saharan Africa (SSA) in keeping with the steady increase in cardiovascular risk factors for coronary artery disease (CAD). • The prevalence of CAD in African patients with heart failure with reduced ejection fraction (HFrEF) was 52.3%. • In the multivariable logistic regression, diabetic mellitus, pathological Q waves, significant ST segment deviation, and regional wall motion abnormalities were significantly associated with CAD.

Deep learning approaches have demonstrated great achievements in the field of computer-aided medical image analysis, improving the precision of diagnosis across a range of medical disorders. These developments have not, however, been immune to the appearance of adversarial attacks, creating the possibility of incorrect diagnosis with substantial clinical implications. Concurrently, the field has seen notable advancements in defending against such targeted adversary intrusions in deep medical diagnostic systems. In the context of medical image analysis, this article provides a comprehensive survey of current advancements in adversarial attacks and their accompanying defensive strategies. In addition, a comprehensive conceptual analysis is presented, including several adversarial attacks and defensive strategies designed for the interpretation of medical images. This survey, which draws on qualitative and quantitative findings, concludes with a thorough discussion of the problems with adversarial attack and defensive mechanisms that are unique to medical image analysis systems, opening up new directions for future research. We identified that the main problems with adversarial attack and defense in medical imaging include dataset and labeling, computational resources, robustness against target attacks, evaluation of transferability and adaptability, interpretability and explainability, real-time detection and response, and adversarial attacks in multi-modal fusion. The area of medical imaging adversarial attack and defensive mechanisms might move toward more secure, dependable, and therapeutically useful deep learning systems by filling in these research gaps and following these future objectives.

The economy of Kenya depends mainly on agriculture where smallholder farming has a significant role as it employs 65 percent of the work force and contributes 32 percent of Kenya’s GDP. However, the agricultural industry in Kenya is currently facing difficulties in low productivity. The rural areas have the largest concentration of poverty and food insecurity. Majority of the farming activities in Kenya are on small scale and the problems of these farmers are multifaceted including sub-divisions and small farm sizes, leading to diseconomies of scale and low productivity. The goal of this research was to develop and validate an E-agriculture Framework for Improving Agricultural Productivity among the Smallholder Farmers. Descriptive research design was used. The study was carried out in South Eastern Kenya. The target population comprised 224 meteorological staff, 421 agricultural extension officers, 208 ICT personnel and 3,833 farmers. Data was collected using self-administered questionnaires, observation and interviews and analyzed using SPSS. The study found that challenges faced farmers were cost, illiteracy and ICT skills among others. Further, the study established that farmers required specific information such as soil management, pest management etc., for mainly improving their productivity. The researcher proposed an e-agriculture framework for improving agricultural productivity through promoting innovative use of ICT tools to bridge the distance between the farmers and the research communities. The proposed e-framework could be used by government policy makers and stakeholders on ICT on agricultural services in other developing countries to implement policies that speeded up the use of ICT on agricultural information.