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Barriers to Diabetes Self-Management in Grenada During the Covid-19 Pandemic: A Qualitative Study
Get PDFDuring the COVID-19 lockdown, several countries implemented restrictions that affected how persons with diabetes managed their condition. While several studies exploring diabetes self-management during the pandemic was conducted, none was done in Grenada or the Caribbean region. Therefore, the aim of this study was to identify the barriers to diabetes self-management during the COVID-19 lockdown in Grenada. The study was a descriptive qualitative study with a phenomenological approach. Semi-structured interviews were conducted with 13 participants with type 2 diabetes in Grenada over two months. Two overarching themes emerged, reflecting external and internal barriers to diabetes self-management activities. The results indicated that these personal and environmental barriers significantly affected adherence across the five self-management behaviors. The findings may be used to develop a multidisciplinary approach to improve self-management skills and attitudes and promote appropriate diabetes disaster planning for a future pandemic. Addressing those barriers to diabetes self-management will improve health outcomes and quality of life
Diabetes Management
Get PDFDiabetes is a long-term metabolic condition characterized by high blood sugar levels (hyperglycaemia). It is a primary cause of illness and mortality around the world, and its incidence is increasing at an alarming rate. Diabetes affected an estimated 463 million persons in 2019, with the number expected to rise to 783 million by 2045. The increasing prevalence of diabetes is a major public health concern, and it is essential to implement effective strategies for prevention and management. Diabetes management is a complex task that requires a multidisciplinary approach involving healthcare professionals, patients, and their families
Potential Rheumatological Heart Disease Causing Triple Valve Replacement: A Case Report
Get PDFINTRODUCTION: Mechanical valves were identified in the aortic, mitral, and tricuspid valves of an 88-year-old donor. The presence of these valves along with the donor's past medical history and body habitus indicate a triple valve replacement surgery was performed.
CASE PRESENTATION: Here we describe our 88-year-old donor’s body habitus during routine anatomical dissection.
DISCUSSION: Evidence of a rare triple valve surgery is discussed along with how this type of case report acts as a useful exercise contributing towards medical student education.
CONCLUSION: A rare triple valve replacement appears to have been performed on our donor
Effectiveness of CAM (Complementary and Alternative Medicine) on Varicose Vein Complications
Get PDFThe Varicose vein disease (VVD) is characterized by the enlargement and outward bulging of the veins in the legs. The majority of persons with varicose veins hardly ever see meaningful relief from standard medical treatment. The comprehensive approach of complementary and alternative medicine (CAM) can be used jointly or separately to prevent, minimize, and treat the condition known as enhanced valve competence. Yoga, Ayurveda, Siddha, Homeopathy, and Naturopathy are just a few of the many alternative therapies available through CAM that are affordable. Numerous experimental findings revealed that the alternative therapy works by modifying the hs-CRP protein, enhancing apoptosis, and lowering homocysteine concentration to alleviate the symptoms of varicose vein problems and associated issues
Modernized Management of Biomedical Waste Assisted with Artificial Intelligence
Get PDFBiomedical waste can lead to severe environmental pollution and pose public health risks if not properly handled or disposed of. The efficient management of biomedical waste poses a significant challenge to healthcare facilities, environmental agencies, and regulatory bodies. Traditional management methods often fall short of efficient handling of biomedical waste due to its enormous quantity, diverse, and complex nature. In recent years, different approaches employing Artificial Intelligence (AI) techniques have been introduced and have shown promising potential in biomedical waste management. Wireless detection and IoT methods have enabled the monitoring of waste bins, predictions for the amount of waste, and optimization of the performance of waste processing facilities. This review paper aims to explore the application of AI through machine learning and deep learning models in optimizing the collection, segregation, transportation, disposal, and monitoring processes, which leads to improved resource allocation with risk mitigation of biomedical waste along with prediction, and decision-making using AI algorithms
DNA Computing: A Paradigm Shift from Silicon to Carbon
Get PDFDNA computing, a fascinating frontier in the realm of biological computing, marks a paradigm shift from traditional silicon-based processing to the innovative realm of carbon-based computation. Rooted in the principles of molecular biology, DNA computing harnesses the inherent parallelism of biological systems, offering a revolutionary approach to data storage, processing, and solving complex problems
Review of Bioinformatics Tools and Techniques to Accelerate Ovarian Cancer Research
Get PDFSince the history of humans there was no definitive cure for cancer. The rapid development in the field of bioinformatics has resulted in acceleration of advancement of cancer research. As computing and IT technology improves over time the use and importance of bioinformatics will also rise. The bulk of biological data created by biomedical researchers has increased over the years, and it has become difficult to store and analyze that data. Faster computer processors and advancement in quantum computing will solve the conventional problem of slow data processing and will make the use of bioinformatics even attractive for scientists and researchers across the globe. The success of potential drug candidates and vaccines were identified and credit goes to bioinformatics gene simulation sequencing, simulation and fast data processing. The results were development of a vaccine in record time all thanks to bioinformatics approaches. This paper explores the contribution that bioinformatics has been able to make in the field of ovarian cancer and how the use of DNA sequencing and simulation helped in developing targeted drugs such as PARP inhibitors. It also elucidates the impact bioinformatics can make in developing effective therapies in times to come. Genome sequencing has paved the way in understanding the disease, possible treatment options analyze mutations and further predict the drug target. In this review we will highlight different aspects of bioinformatics tools and techniques that have accelerated the ovarian cancer research
Advancements in Neuroradiology via Artificial Intelligence and Machine Learning
Get PDFNeuroradiology is significantly showing the broad impact in field of Artificial intelligence research and also in Machine learning. Neuro-radiology includes methods such as neuro-imaging which simply diagnose and characterize disorders of the CNS and PNS. Artificial Intelligence (AI) is one of the main attribute in the field of computer science generally focusing on creating "algorithms" which can be used to solve any arbitrary desired problem. AI has several applications in the field of Neuroradiolody and one of the most common and influencing application is machine learning. Machine learning is a data science approach that allows computers to learn without being programmed with specific rules. Some of the factors which shows neuroradiological impact on AI research are; (a) neuroimaging comprising rich, multicontrast, multidimensional, and multimodality data which fit themselves well to machine learning tasks; (b) consideration of well-established neuroimaging public datasets of various neural diseases such as Alzheimer disease, Parkinson disease, tumors, different forms of sclerosis etc. (c) quantitative neuroimaging research history which proves clinical practices. Another major application is Deep learning which is useful in management of information content of digital pictures that a human reader can only identify and use partially. Except this various limitations also come in the picture such as adoption in neuroradiology practice etc. Till now several research has been done which connects the concepts of Neuroradiology and Artificial intelligence and yet more to be done so as to overcome the limitations of AI in Neuroradiology
A Case Report on Carpal Synostosis in an Eight-Year-Old Male
Get PDFIntroduction: Carpal synostosis is a medical condition in which adjacent carpal bones become fused with or without other associated limb deformities. According to literature, carpal synostosis has a relatively low incidence rate of 0.1%. Case report: We report a case of an isolated complete lunotriquetral synostosis of an eight year-old male revealed incidentally upon x-ray examination to rule out fracture of the distal forearm post trauma. Discussion: There is but little literature of an isolated carpal coalition of a pediatric at the time of this report. Also, there is no standardized classification system for carpal coalition due to insufficient imaging data by virtue of rarity of the condition and incomprehensive description of the morphology of coalitions, among others. Though patient’s lunotriquetral synostosis was not seen to impair wrist function, the radiologist report revealed negative ulnar variance, thus the need for further investigation into its possible association. Conclusion: This report adds up to existing literature to contribute a better classification system of carpal synostosis. Association between carpal synostosis and ulnar variance should be further explored
Longitudinal Changes in Depression Among Patients at an Integrated Primary Care Clinic During the COVID-19 Pandemic
Get PDFIntroduction: The current study assessed trajectory of within subject change in depressive symptoms before and after the COVID-19 related lockdowns were implemented in the United States in 2019-2020.
Method: A General Estimating Equations model was conducted with electronic medical records data of 36,868 adult patients at a chain of federally funded integrated primary care clinics. Changes in Patient Health Questionnaire-2 (PHQ-2) scores were included in the model as the dependent variable.
Results: April 2020 was the only month when PHQ-2 scores increased with 95% confidence. April and December 2020 had greater likelihood than April and December 2019 to show a mean increase in depressive symptoms.
Discussion: Depression rates increased substantially at the start of the pandemic (i.e., April 2020) and subsequently returned to pre-pandemic expectations. However, depression rates were less likely to decline in December 2019, which may be due to social distancing and cancellation of holiday gatherings