County-level residential segregation and sedentary behavior in US adults.

Background: Excessive sedentary behavior (SB) is highly prevalent among adults in the United States (US). From a socio-ecological perspective, residential segregation may affect SB; however, this remains understudied. Thus, we aimed to examine associations between county-level segregation and sedentary time in a nationwide sample of US adults.

Impact of dualism on the perception of treatability in psychiatry.

A false division between mental and physical disorders is supported by dualism, contributing to mental health stigma. There is a widespread misconception about the prognosis and treatment options for psychiatric diseases. This is despite data supporting the effectiveness of psychiatric treatments for a variety of illnesses that have been proven by meta-analysis.

The effect of crocetin (a saffron carotenoid) supplementation on antioxidant and inflammatory indexes and serum leptin concentration in patients with coronary artery disease.

: Coronary artery disease (CAD) is a common heart disease characterized by plaque buildup in the coronary arteries. Saffron, which is rich in active compounds, has strong antioxidant properties that help reduce free radicals and plasma malondialdehyde (MDA) levels. This study aimed to evaluate the effects of crocetin supplementation on antioxidant and inflammatory markers, as well as serum leptin levels, in CAD patients.

Efficacy of using a digital health intervention model using community health workers for primary health services in Bangladesh: a repeated cross-sectional observational study.

Objective: This study aims to evaluate the effectiveness of a digital health intervention model by observing people's health conditions in a rural area of Bangladesh. Through a repeated cross-sectional design, health outcomes were assessed at six-month intervals over 18 months.

Methods: The data presented in this paper are obtained from the model's pilot implementation in one catchment area in Bangladesh.

Artificial intelligence for early detection of diabetes mellitus complications via retinal imaging.

Background: Diabetes mellitus (DM) increases the risk of vascular complications, and retinal vasculature imaging serves as a valuable indicator of both microvascular and macrovascular health. Moreover, artificial intelligence (AI)-enabled systems developed for high-throughput detection of diabetic retinopathy (DR) using digitized retinal images have become clinically adopted. This study reviews AI applications using retinal images for DM-related complications, highlighting advancements beyond DR screening, diagnosis, and prognosis, and addresses implementation challenges, such as ethics, data privacy, equitable access, and explainability.

Digital Home-Based Self-Monitoring System for People with Heart Failure: Protocol for Development of SmartHeart and Evaluation of Feasibility and Acceptability.

Background: Heart failure (HF) is a chronic, progressive condition where the heart cannot pump enough blood to meet the body's needs. In addition to the daily challenges that HF poses, acute exacerbations can lead to costly hospitalizations and increased mortality. High health care costs and the burden of HF have led to the emerging application of new technologies to support people living with HF to stay well while living in the community.

Association of Cardiovascular Disease Risk Factors With Estimated Dietary Salt Consumption in Bangladeshi Adults: A Nationally Representative Cross-Sectional Study.

This population-based, nationally representative cross-sectional study assessed the daily salt consumption status and its associated cardiovascular disease (CVD) risk factors using weighted data from the STEPwise approach to noncommunicable disease risk factor surveillance conducted in 2018 in Bangladesh. It included a non-institutionalized adults' population of 6189 men and women aged 18-69 years. Their daily salt consumption was estimated using the spot urine sodium concentration following the Tanaka equation and reported according to the standard nomenclature proposed by the World Hypertension League and partner organizations involved in dietary salt reduction.

Enhancing stroke disease classification through machine learning models via a novel voting system by feature selection techniques.

Heart disease remains a leading cause of mortality and morbidity worldwide, necessitating the development of accurate and reliable predictive models to facilitate early detection and intervention. While state of the art work has focused on various machine learning approaches for predicting heart disease, but they could not able to achieve remarkable accuracy. In response to this need, we applied nine machine learning algorithms XGBoost, logistic regression, decision tree, random forest, k-nearest neighbors (KNN), support vector machine (SVM), gaussian naïve bayes (NB gaussian), adaptive boosting, and linear regression to predict heart disease based on a range of physiological indicators.

Discrepancies between pre-specified and reported primary outcomes: A cross-sectional analysis of randomized controlled trials in gastroenterology and hepatology journals.

Background: Previous research has raised concerns regarding inconsistencies between reported and pre-specified outcomes in randomized controlled trials (RCTs) across various biomedical disciplines. However, studies examining whether similar discrepancies exist in RCTs focusing on gastrointestinal and liver diseases are limited. This study aimed to assess the extent of discrepancies between registered and published primary outcomes in RCTs featured in journals specializing in gastroenterology and hepatology.

Stakeholder perceptions of factors contributing to effective implementation of exercise cardiac telerehabilitation in clinical practice.

Aims: Cardiac exercise telerehabilitation is effective and can be cost-effective for managing ischaemic heart disease, but implementation of evidence-based interventions in clinical practice remains a challenge. We aimed to identify factors that cardiac rehabilitation stakeholders perceived could influence the effectiveness of implementing an evidence-based, real-time remotely monitored cardiac exercise telerehabilitation intervention (REMOTE-CR).

Methods And Results: Online interviews and focus groups were conducted with cardiac rehabilitation consumers (n = 16, 5 female, 61.

Health and wellbeing of staff working at higher education institutions globally during the post-COVID-19 pandemic period: evidence from a cross-sectional study.

Background: The ongoing global crisis of Higher Education (HE) institutions during the post-COVID-19 pandemic period has increased the likelihood of enduring psychological stressors for staff. This study aimed to identify factors associated with job insecurity, burnout, psychological distress and coping amongst staff working at HE institutions globally.

Methods: An anonymous cross-sectional study was conducted in 2023 with staff at HE institutions across 16 countries.

A control system model of capability-opportunity-motivation and behaviour (COM-B) framework for sedentary and physical activity behaviours.

Objective: Theoretical frameworks are essential for understanding behaviour change, yet their current use is inadequate to capture the complexity of human behaviour such as physical activity. Real-time and big data analytics can assist in the development of more testable and dynamic models of current theories. To transform current behavioural theories into more dynamic models, it is recommended that researchers adopt principles such as control systems engineering.

The burden of cardiovascular disease attributable to high dietary sodium intake in Australia between 1990 and 2019.

Background: Diets high in sodium are associated with adverse cardiovascular outcomes. We aimed to quantify the burden of cardiovascular disease (CVD) attributable to high dietary sodium consumption in the Australian population.

Methods: Using data from the Global Burden of Disease (GBD) 2019, we estimated the age-standardised rates (per 100 000 population) and the total numbers of years lived with a disability (YLDs), years of life lost (YLLs), disability-adjusted life years (DALYs), and deaths for CVD attributable to high sodium (≥1000 mg/day) consumption in the Australian population, by sex and age groups (≥25 years) between 1990 and 2019.

The contribution of raised blood pressure to all-cause and cardiovascular deaths and disability-adjusted life-years (DALYs) in Australia: Analysis of global burden of disease study from 1990 to 2019.

Aims: In a high-income country, Australia, it is unclear how raised systolic blood pressure (SBP) ranks among other risk factors regarding the overall and cardiovascular disease (CVD) burden, and whether the situation has changed over time.

Methods: We analysed the 2019 Global Burden of Disease (GBD) data, with focus on Australia. We assessed ten leading risk factors for all-cause and CVD deaths and disability-adjusted life-years (DALYs) and compared findings with the Australian Burden of Diseases Study.

Non-invasive blood glucose monitoring technology in diabetes management: review.

Diabetes is one of the leading non-communicable diseases globally, adversely impacting an individual's quality of life and adding a considerable burden to the healthcare systems. The necessity for frequent blood glucose (BG) monitoring and the inconveniences associated with self-monitoring of BG, such as pain and discomfort, has motivated the development of non-invasive BG approaches. However, the current research progress is slow, and only a few BG self-monitoring devices have made considerable progress.

The Effect of Adding Mirtazapine to Quetiapine on Reducing Agitation in Patients with Alzheimer's Disease.

Background: Alzheimer's disease (AD) is one of the most debilitating diseases in old age, associated with cognitive decline and behavioral symptoms.

Objective: This study aimed to investigate the effect of adding mirtazapine to quetiapine in reducing agitation among patients with AD.

Methods: Thirty-seven elderly patients (18 cases and 19 controls) with AD, diagnosed according to National Institute on Aging and Alzheimer's Association (NIA-AA) criteria, were enrolled at Nezam-Mafi Clinic.

A Bluetooth-Enabled Device for Real-Time Detection of Sitting, Standing, and Walking: Cross-Sectional Validation Study.

Background: This study assesses the accuracy of a Bluetooth-enabled prototype activity tracker called the Sedentary behaviOR Detector (SORD) device in identifying sedentary, standing, and walking behaviors in a group of adult participants.

Objective: The primary objective of this study was to determine the criterion and convergent validity of SORD against direct observation and activPAL.

Methods: A total of 15 healthy adults wore SORD and activPAL devices on their thighs while engaging in activities (lying, reclining, sitting, standing, and walking).

NeuroNet19: an explainable deep neural network model for the classification of brain tumors using magnetic resonance imaging data.

Brain tumors (BTs) are one of the deadliest diseases that can significantly shorten a person's life. In recent years, deep learning has become increasingly popular for detecting and classifying BTs. In this paper, we propose a deep neural network architecture called NeuroNet19.

The burden of cardiovascular disease attributable to dietary risk factors in Australia between 1990 and 2019.

Unhealthy diet is associated with increased risk of cardiovascular diseases (CVD). However, there are no studies reporting the impact and trends of dietary risk factors on CVD in Australia. This study aimed to determine the burden of CVDs attributable to dietary risk factors in Australia between 1990 and 2019.

Associations of adherence to the DASH diet and Mediterranean diet with maternal c-reactive protein levels during pregnancy.

Background And Aims: Elevated C-reactive protein (CRP) during pregnancy, a marker of inflammation, is associated with adverse outcomes. Better understanding the relationship between CRP and modifiable factors, including diet, is essential to assist early pregnancy lifestyle interventions. The aim of this study was to assess the relationship between adherence to the Dietary Approaches to Stop Hypertension diet (DASH-diet) and the Mediterranean diet (MED-diet) during pregnancy with maternal plasma CRP in early and late pregnancy.