Parity of esteem: A global COVID-19 vaccination approach for people with mental illnesses, based on facts from 34 countries; recommendations and solutions.

Background: The coronavirus disease (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has detrimental effects on physical and mental health. Patients with severe mental illness are at higher risk of contracting the virus due to social determinants of health. Vulnerable populations include the elderly, people with pre-existing conditions, and those exposed to SARS-CoV-2. Unfortunately, only a few countries have updated vaccination strategies to prioritize patients with mental illnesses. Therefore, we aimed to explore whether individuals with mental disorders are prioritized in vaccine allocation strategies in different world regions. They are often neglected in policymaking but are highly vulnerable to the threatening complications of COVID-19. Methods: A questionnaire was developed to record details regarding COVID-19 vaccination and prioritizations for groups of persons with non-communicable diseases (NCDs), mental disorders, and substance use disorders (SUDs). NCDs were defined according to the WHO as chronic diseases that are the result of a combination of genetic, physiological, environmental, and behavioral factors such as cardiovascular diseases, cancer, respiratory diseases, and diabetes. Results: Most countries surveyed (80%) reported healthcare delivery via a nationalized health service. It was found that 82% of the countries had set up advisory groups, but only 26% included a mental health professional. Most frequently, malignancy (68%) was prioritized followed by diabetes type 2 (62%) and type 1 (59%). Only nine countries (26%) prioritized mental health conditions. Conclusion: The spread of the coronavirus has exposed both the strengths and flaws of our healthcare systems. The most vulnerable groups suffered the most and were hit first and faced most challenges. These findings raise awareness that patients with mental illnesses have been overlooked in immunization campaigns. The range of their mortality, morbidity, and quality of life could have widened due to this delay.

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. In this article, we aim to describe a control system model of capability-opportunity-motivation and behaviour (COM-B) framework for reducing sedentary behaviour (SB) and increasing physical activity (PA) in adults. Methods: The COM-B model is explained in terms of control systems. Examples of effective behaviour change techniques (BCTs) (e.g. goal setting, problem-solving and social support) for reducing SB and increasing PA were mapped to the COM-B model for illustration. Result: A fluid analogy of the COM-B system is presented. Conclusions: The proposed integrated model will enable empirical testing of individual behaviour change components (i.e. BCTs) and contribute to the optimisation of digital behaviour change interventions.

Referral Network Pathways of Care for Psychiatric Disorders in Kashmir - A Study from India. / Kesmir'de Psikiyatrik Bozukluklarin Tedavisine Yönelik Sevk Yollari - Hindistan'dan Bir Çalisma.

OBJECTIVE: Access to psychiatry services in Kashmir is challenging because of active enduring conflict, insecurity and a fundamental role played by the traditional health workers. We aimed to assess the main pathways to mental health services in Kashmir, India. METHODS: This cross-sectional hospital-based study was performed from March 2012 to June 2017 in the outpatient psychiatry department at a psychiatric disease hospital in Kashmir. A convenience sampling method was used to select newly referred patients to the services. A survey was developed to collect information on demographic data and the main pathways for patients when seeking care for mental disorders. RESULTS: A total of 518 patients were interviewed. About half of the respondents (48.8 %) attended clinical consultation from a general pathway like a physician or a neurologist, while 31.8% were visiting a psychiatrist for a significant psychiatric disorder. For some patients (17.8%), their initial pathway to mental health services is traditional healers. CONCLUSION: The current study revealed different pathways to seeking psychiatric care in Kashmir India. Further studies are needed to address the treatment gap and ways to improve access to mental health services for the Kashmir population.

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 study compared Australian estimates with similar high-income countries (Group of 20 [G20] members). RESULTS: From 1990 to 2019, the age-standardized rates of CVD deaths, DALYs, YLDs, and YLLs per 100 000 population in Australia attributable to high sodium decreased. However, between 2013 and 2019, the total number of CVD deaths increased, and the number of CVD YLDs increased exponentially for both sexes for the whole period between 1990 and 2019. Men had a two-fold higher rate for high sodium CVD burden, compared to females between 1990 to 2019. Individuals aged between 80 and 84 years had the highest rates of CVD burden during the same period; however, older age groups reported the greatest decline in CVD burden compared to young and middle-aged adults in Australia. The age-standardised rates for high sodium attributable CVD consistently contributed more towards DALYs than YLDs in 2019 for both sexes. When compared to G20 countries, Australians displayed the lowest age-standardized rates for CVD deaths, DALYs, YLDs, and YLLs alongside Turkey, France, and the United Kingdom in 2019. CONCLUSION: While age-standardized CVD burden attributable to high sodium consumption decreased for both sexes over the past 30 years, the total number of CVD deaths showed an increase between 2013 and 2019. This study underscores the need for sustained efforts to address the rising absolute number of CVD deaths, especially among men and older people, and emphasizes the importance of continued vigilance in monitoring and implementing strategies to reduce the impact of high sodium consumption on cardiovascular health in Australia.

AlcoChange: A digital therapeutic for patients with alcohol-related liver disease.

Background & Aims: Maintenance of abstinence in alcohol-related liver disease (ARLD) is a major unmet therapeutic need. Digital therapeutics can deliver ongoing behavioural therapy, in real-time, for chronic conditions. The aim of this project was to develop and clinically test AlcoChange, a novel digital therapeutic for ARLD. Methods: AlcoChange was developed using validated behaviour change techniques and a digital alcohol breathalyser. This was an open-label, single-centre study. Patients with ARLD, ongoing alcohol use (within 1 month) and possession of a suitable smartphone were eligible. Patients were recruited from inpatient and outpatient settings, and received AlcoChange therapy for 3 months. The primary outcome was reduction in alcohol use from baseline to 3 months, measured by timeline follow-back. Secondary outcomes included: (i) compliance with the AlcoChange app, (ii) alcohol-related and all-cause hospital re-admissions up to 1 year, (iii) qualitative analysis to determine factors associated with compliance. Results: Sixty-five patients were recruited, of whom 41 completed the study per protocol. Patients compliant with the intervention (>60 logins over 3 months) had a significant reduction in alcohol use from baseline compared to non-compliant patients (median [IQR]: -100% [100% to -55.1%] vs. -57.1% [-95.3% to +32.13%], p = 0.029). The proportion attaining abstinence at 3 months was higher in the compliant group (57.1% vs. 22.2%, p = 0.025). The compliant group had a significantly decreased risk of subsequent alcohol-related re-admission up to 12 months (p = 0.008). Qualitative analysis demonstrated that receiving in-app feedback and the presence of a health-related 'sentinel event' were predictors of compliance with the intervention. Conclusions: Use of the novel digital therapeutic, AlcoChange, was associated with a significant reduction in alcohol use and an increase in the proportion of patients with ARLD attaining abstinence. Definitive randomised trials are warranted for this intervention. Impact and implications: Alcohol-related liver disease (ARLD) is an increasing health problem worldwide. The main cause of death and disability in ARLD is ongoing alcohol consumption, but few patients receive medications or talking therapy to maintain abstinence. This study demonstrated that a digital therapeutic, linked to a smartphone, may help reduce alcohol consumption and alcohol-related hospital admissions in these patients. If validated in larger, randomised, trials, digital therapeutics may have a role in the primary and secondary prevention of complicatons from ARLD.

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. RESULTS: From 1990 to 2019, raised SBP remained the leading risk factor for attributable all-cause deaths (followed by dietary risks and tobacco use), accounting for 29,056/75,235 (95% Uncertainty Interval (UI) [24,863 to 32,915]) deaths in 1990; 21,845/76,893 [17,678 to 26,044] in 2010; and 25,498/90,393 [20,152 to 30,851] in 2019. Contributions of raised SBP to cardiovascular deaths for both sexes were 54.0% [45.8 to 61.5] in 1990, 44.0% [36.7 to 51.3] in 2010 and 43.7% [36.2 to 51.6] in 2019, respectively. The contribution of raised SBP to cardiovascular deaths declined between 1990 and 2010 but exhibited an increase in males from 2010 onwards, with figures of 52.6% [44.7 to 60.0] in 1990, 43.1% [36.0 to 50.5] in 2010 and 43.5% [35.7 to 51.4] in 2019. The contribution of raised SBP to stroke deaths and DALYs in males aged 25-49 years were higher than other age groups, in excess of 60% and increasing steeply between 2010 and 2019. CONCLUSION: Raised SBP continues to be the leading risk factor for all-cause and cardiovascular deaths in Australia. We urge cross-disciplinary stakeholder engagement to implement effective strategies to detect, treat and control raised blood pressure as a central priority to mitigate the CVD burden.

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. Inclusion criteria comprised a minimum of two years post-diagnosis, a Cohen-Mansfield Agitation and Aggression Questionnaire (CMAI) score above 45, and treatment with 100-150 mg of quetiapine. Patients were randomly assigned to receive mirtazapine (15 mg at night, increased to 30 mg at night after two weeks) or a placebo. Cognitive changes were assessed at weeks 0 and 6 using the Mini-Mental State Examination instrument. Furthermore, symptoms of agitation and aggression were evaluated using the CMAI questionnaire at weeks 4 and 6. Results: In this study, the mean duration of AD in the control group was 4.68 years, and in the case group, it was 5.05 years. Although the total agitation score showed no significant change at the end of the study compared to the control group, the rate of physical non-aggressive behavior showed a significant decrease (p <  0.05). Conclusions: According to this study, adding mirtazapine to the antipsychotic drug regimen may not be an effective treatment for agitation in AD patients.

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. Hence, we evaluate the available non-invasive glucose monitoring technologies validated against BG recordings to provide future research direction to design, develop, and deploy self-monitoring of BG with integrated emerging technologies. We searched five databases, Embase, MEDLINE, Proquest, Scopus, and Web of Science, to assess the non-invasive technology's scope in the diabetes management paradigm published from 2000 to 2020. A total of three approaches to non-invasive screening, including saliva, skin, and breath, were identified and discussed. We observed a statistical relationship between BG measurements obtained from non-invasive methods and standard clinical measures. Opportunities exist for future research to advance research progress and facilitate early technology adoption for healthcare practice. The results promise clinical validity; however, formulating regulatory guidelines could foresee the deployment of approved non-invasive BG monitoring technologies in healthcare practice. Further, research prospects are there to design, develop, and deploy integrated diabetes management systems with mobile technologies, data analytics, and the internet of things (IoT) to deliver a personalised monitoring system.

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. It utilizes VGG19 as its backbone and incorporates a novel module named the Inverted Pyramid Pooling Module (iPPM). The iPPM captures multi-scale feature maps, ensuring the extraction of both local and global image contexts. This enhances the feature maps produced by the backbone, regardless of the spatial positioning or size of the tumors. To ensure the model's transparency and accountability, we employ Explainable AI. Specifically, we use Local Interpretable Model-Agnostic Explanations (LIME), which highlights the features or areas focused on while predicting individual images. NeuroNet19 is trained on four classes of BTs: glioma, meningioma, no tumor, and pituitary tumors. It is tested on a public dataset containing 7023 images. Our research demonstrates that NeuroNet19 achieves the highest accuracy at 99.3%, with precision, recall, and F1 scores at 99.2% and a Cohen Kappa coefficient (CKC) of 99%.

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. We used data from the Global Burden of Diseases (GBD) study and quantified the rate (per 100,000) of deaths, disability-adjusted life years (DALYs), years lived with a disability (YLDs), and years of life lost (YLLs) for 21 CVDs attributable to 13 dietary risk factors (eight food groups and five nutrients) in Australia by sex and age groups (≥25 years and over). In 2019, the age-standardised rates of deaths, YLDs, YLLs, and DALYs attributable to dietary risk factors attributable to CVDs in the Australian population were 26.5, 60.8, 349.9, and 410.8 per 100,000 in women and 46.1, 62.6, 807.0, and 869.6 in men. Between 1990 and 2019, YLLs consistently contributed more towards the rates of DALYs than YLDs. Over the 30-year period, CVD deaths, YLLs, and DALYs attributable to dietary risk factors declined in both women and men. The leading dietary risk factors for CVD deaths and DALYs were a diet high in red meat (6.1 deaths per 100,000 [3.6, 8.7] and 115.6 DALYs per 100,000 [79.7, 151.6]) in women and a diet low in wholegrains (11.3 deaths [4.4, 15.1] and 220.3 DALYs [86.4, 291.8]) in men. Sex differences were observed in the contribution of dietary risk factors to CVD over time such that the lowest rate of decrease in deaths and DALYs occurred with diets high in sodium in women and diets high in processed meat in men. Although the burden of diet-related CVD has decreased significantly in the Australian population over the past 30 years, diets low in wholegrains and high in red meat continue to contribute significantly to the overall CVD burden. Future nutrition programs and policies should target these dietary risk factors.

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. METHODS AND RESULTS: Secondary analysis of the Creatine and Pregnancy Outcomes (CPO) study was undertaken. Women (n = 215) attending antenatal clinics through Monash Health, Melbourne were recruited at 10-20 weeks gestation. Medical history and blood samples were collected at 5 antenatal visits. Adapted DASH-diet and MED-diet scores were calculated from Food Frequency Questionnaires completed at early ([mean ± SD]) (15 ± 3 weeks) and late (36 ± 1 week) pregnancy. CRP was measured in maternal plasma samples collected at the same time points. Adjusted linear regression models assessed associations of early-pregnancy DASH and MED-diet scores with early and late pregnancy plasma CRP. There were no statistically significant changes in DASH-diet score from early (23.5 ± 4.8) to late (23.5 ± 5.2) pregnancy (p = 0.97) or MED-diet score from early (3.99 ± 1.6) to late pregnancy (4.08 ± 1.8) (p = 0.41). At early-pregnancy, there was an inverse relationship between DASH-diet scores and MED-diet scores with plasma CRP; (ß = -0.04 [95%CI = -0.07, -0.00], p = 0.044), (ß = -0.12 [95%CI = -0.21, -0.02], p = 0.023). CONCLUSION: Adherence to the DASH-diet and MED-diet during early pregnancy may be beneficial in reducing inflammation. Assessment of maternal dietary patterns may assist development of preventive strategies, including dietary modification, to optimise maternal cardiometabolic health in pregnancy.

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). Direct observation was facilitated with cameras. Algorithms were developed using the Python programming language. The Bland-Altman method was used to assess the level of agreement. RESULTS: Overall, 1 model generated a low level of bias and high precision for SORD. In this model, accuracy, sensitivity, and specificity were all above 0.95 for detecting sitting, reclining, standing, and walking. Bland-Altman results showed that mean biases between SORD and direct observation were 0.3% for sitting and reclining (limits of agreement [LoA]=-0.3% to 0.9%), 1.19% for standing (LoA=-1.5% to 3.42%), and -4.71% for walking (LoA=-9.26% to -0.16%). The mean biases between SORD and activPAL were -3.45% for sitting and reclining (LoA=-11.59% to 4.68%), 7.45% for standing (LoA=-5.04% to 19.95%), and -5.40% for walking (LoA=-11.44% to 0.64%). CONCLUSIONS: Results suggest that SORD is a valid device for detecting sitting, standing, and walking, which was demonstrated by excellent accuracy compared to direct observation. SORD offers promise for future inclusion in theory-based, real-time, and adaptive interventions to encourage physical activity and reduce sedentary behavior.

Prevalence and determinants of hypertension in South-Asian Urban Communities: findings from Demographic and Health Surveys (DHS) data of South Asian countries.

Hypertension increases risk of stroke and other cardiovascular diseases, however, its prevalence and determinants in South Asian urban communities using country representative community-based datasets is lacking. This study evaluated prevalence of hypertension and it's determinants among urban residents of three South Asian countries. Urban population data from demographic and health surveys in Bangladesh, India, and Nepal were extracted. Hypertension prevalence was defined as systolic/diastolic blood pressure ≥ 140/ 90 mmHg. Age, education, wealth, physical activity, alcohol, BMI were considered as risk factors associated with the increased risk of hypertension. We performed binary logistic regression and calculated adjusted Odds Ratios (AOR) with 95% confidence interval (CI) to assess factors related to hypertension. Hypertension prevalence was 37.4% in India, 25.1% in Bangladesh and 18.4% in Nepal. Prevalence increased with age in all settings. Females had reduced odds of hypertension in Bangladesh (AOR 0.75; CI: 0.69, 0.81) and Nepal (AOR 0.62; CI: 0.54, 0.71), but higher risk in India (AOR 2.54; CI: 2.45, 2.63). Low education, caffeine consumption, obesity was associated with higher prevalence of hypertension in all three countries. Smokers had increased odds of hypertension in India (AOR 1.11; CI: 1.06, 1.15) and Nepal (AOR 1.23; 1.02, 1.47). Overall, hypertension prevalence is high in all three countries. Modifiable socioeconomic and lifestyle factors (education, wealth index, smoking status, caffeine consumption and BMI) associated with hypertension. Comprehensive hypertension pacific and sensitive interventions (including behavioral modification treatments and timely screening and access to health care) are urgently needed to prevent and control hypertension among urban populations in South Asia.

Time-domain heart rate variability features for automatic congestive heart failure prediction.

AIMS: Heart failure is a serious condition that often goes undiagnosed in primary care due to the lack of reliable diagnostic tools and the similarity of its symptoms with other diseases. Non-invasive monitoring of heart rate variability (HRV), which reflects the activity of the autonomic nervous system, could offer a novel and accurate way to detect and manage heart failure patients. This study aimed to assess the feasibility of using machine learning techniques on HRV data as a non-invasive biomarker to classify healthy adults and those with heart failure. METHODS AND RESULTS: We used digitized electrocardiogram recordings from 54 adults with normal sinus rhythm and 44 adults categorized into New York Heart Association classes 1, 2, and 3, suffering from congestive heart failure. All recordings were sourced from the PhysioNet database. Following data pre-processing, we performed time-domain HRV analysis on all individual recordings, including root mean square of the successive difference in adjacent RR interval (RRi) (RMSSD), the standard deviation of RRi (SDNN, the NN stands for natural or sinus intervals), the standard deviation of the successive differences between successive RRi (SDSD), the number or percentage of RRi longer than 50 ms (NN50 and pNN50), and the average value of RRi [mean RR interval (mRRi)]. In our experimental classification performance evaluation, on the computed HRV parameters, we optimized hyperparameters and performed five-fold cross-validation using four machine learning classification algorithms: support vector machine, k-nearest neighbour (KNN), naïve Bayes, and decision tree (DT). We evaluated the prediction accuracy of these models using performance criteria, namely, precision, recall, specificity, F1 score, and overall accuracy. For added insight, we also presented receiver operating characteristic (ROC) plots and area under the ROC curve (AUC) values. The overall best performance accuracy of 77% was achieved when KNN and DT were trained on computed HRV parameters with a 5 min time window. KNN obtained an AUC of 0.77, while DT attained 0.78. Additionally, in the classification of severe congestive heart failure, KNN and DT had the best accuracy of 91%, with KNN achieving an AUC of 0.88 and DT obtaining 0.92. CONCLUSIONS: The results show that HRV can accurately predict severe congestive heart failure. The findings of this study could inform the use of machine learning approaches on non-invasive HRV, to screen congestive heart failure individuals in primary care.

Lifestyle management of hypertension: International Society of Hypertension position paper endorsed by the World Hypertension League and European Society of Hypertension.

Hypertension, defined as persistently elevated systolic blood pressure (SBP) >140 mmHg and/or diastolic blood pressure (DBP) at least 90 mmHg (International Society of Hypertension guidelines), affects over 1.5 billion people worldwide. Hypertension is associated with increased risk of cardiovascular disease (CVD) events (e.g. coronary heart disease, heart failure and stroke) and death. An international panel of experts convened by the International Society of Hypertension College of Experts compiled lifestyle management recommendations as first-line strategy to prevent and control hypertension in adulthood. We also recommend that lifestyle changes be continued even when blood pressure-lowering medications are prescribed. Specific recommendations based on literature evidence are summarized with advice to start these measures early in life, including maintaining a healthy body weight, increased levels of different types of physical activity, healthy eating and drinking, avoidance and cessation of smoking and alcohol use, management of stress and sleep levels. We also discuss the relevance of specific approaches including consumption of sodium, potassium, sugar, fibre, coffee, tea, intermittent fasting as well as integrated strategies to implement these recommendations using, for example, behaviour change-related technologies and digital tools.

Developing a Deep Neural Network model for COVID-19 diagnosis based on CT scan images.

COVID-19 is most commonly diagnosed using a testing kit but chest X-rays and computed tomography (CT) scan images have a potential role in COVID-19 diagnosis. Currently, CT diagnosis systems based on Artificial intelligence (AI) models have been used in some countries. Previous research studies used complex neural networks, which led to difficulty in network training and high computation rates. Hence, in this study, we developed the 6-layer Deep Neural Network (DNN) model for COVID-19 diagnosis based on CT scan images. The proposed DNN model is generated to improve accurate diagnostics for classifying sick and healthy persons. Also, other classification models, such as decision trees, random forests and standard neural networks, have been investigated. One of the main contributions of this study is the use of the global feature extractor operator for feature extraction from the images. Furthermore, the 10-fold cross-validation technique is utilized for partitioning the data into training, testing and validation. During the DNN training, the model is generated without dropping out of neurons in the layers. The experimental results of the lightweight DNN model demonstrated that this model has the best accuracy of 96.71% compared to the previous classification models for COVID-19 diagnosis.

The promise of digital healthcare technologies.

Digital health technologies have been in use for many years in a wide spectrum of healthcare scenarios. This narrative review outlines the current use and the future strategies and significance of digital health technologies in modern healthcare applications. It covers the current state of the scientific field (delineating major strengths, limitations, and applications) and envisions the future impact of relevant emerging key technologies. Furthermore, we attempt to provide recommendations for innovative approaches that would accelerate and benefit the research, translation and utilization of digital health technologies.

The burden of ischemic heart disease and the epidemiologic transition in the Eastern Mediterranean Region: 1990-2019.

It has been estimated that in the next decade, IHD prevalence, DALYs and deaths will increase more significantly in EMR than in any other region of the world. This study aims to provide a comprehensive description of the trends in the burden of ischemic heart disease (IHD) across the countries of the Eastern Mediterranean Region (EMR) from 1990 to 2019. Data on IHD prevalence, disability-adjusted life years (DALYs), mortality, DALYs attributable to risk factors, healthcare access and quality index (HAQ), and universal health coverage (UHC) were extracted from the Global Burden of Disease (GBD) database for EMR countries. The data were stratified based on the social demographic index (SDI). Information on cardiac rehabilitation was obtained from publications by the International Council of Cardiovascular Prevention and Rehabilitation (ICCPR), and additional country-specific data were obtained through advanced search methods. Age standardization was performed using the direct method, applying the estimated age structure of the global population from 2019. Uncertainty intervals were calculated through 1000 iterations, and the 2.5th and 97.5th percentiles were derived from these calculations. The age-standardized prevalence of IHD in the EMR increased from 5.0% to 5.5% between 1990 and 2019, while it decreased at the global level. In the EMR, the age-standardized rates of IHD mortality and DALYs decreased by 11.4% and 15.4%, respectively, during the study period, although both rates remained higher than the global rates. The burden of IHD was found to be higher in males compared to females. Bahrain exhibited the highest decrease in age-standardized prevalence (-3.7%), mortality (-65.0%), and DALYs (-69.1%) rates among the EMR countries. Conversely, Oman experienced the highest increase in prevalence (14.5%), while Pakistan had the greatest increase in mortality (30.0%) and DALYs (32.0%) rates. The top three risk factors contributing to IHD DALYs in the EMR in 2019 were high systolic blood pressure, high low-density lipoprotein cholesterol, and particulate matter pollution. The trend analysis over the 29-year period (1990-2019) revealed that high fasting plasma glucose (64.0%) and high body mass index (23.4%) exhibited increasing trends as attributed risk factors for IHD DALYs in the EMR. Our findings indicate an increasing trend in the prevalence of IHD and a decrease in mortality and DALYs in the EMR. These results emphasize the need for well-planned prevention and treatment strategies to address the risk factors associated with IHD. It is crucial for the countries in this region to prioritize the development and implementation of programs focused on health promotion, education, prevention, and medical care.