Brit J Hosp Med
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Hypokalaemia is a common electrolyte disorder affecting hospitalised patients. It is associated with adverse outcomes including increased mortality. Inpatients with hypokalaemia need a different approach to workup and management as the aetiologies and progression of the hypokalaemia are distinct to outpatients. ⋯ This paper reviews the assessment of hypokalaemia in a hospital setting. It is aimed at early career doctors on the wards to help carry out a thorough evaluation. It also provides a useful framework for management.
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Review
Application of Injectable Hydrogels as Delivery Systems in Osteoarthritis and Rheumatoid Arthritis.
Osteoarthritis and rheumatoid arthritis, though etiologically distinct, are both inflammatory joint diseases that cause progressive joint injury, chronic pain, and loss of function. Therefore, long-term treatment with a focus on relieving symptoms is needed. At present, the primary treatment for arthritis is drug therapy, both oral and intravenous. ⋯ This review summarizes the types of injectable hydrogels and analyzes their applications as delivery systems in arthritis treatment. We also explored how hydrogels counteract inflammation, bone and cartilage degradation, and oxidative stress, while promoting joint cartilage regeneration in the treatment of osteoarthritis (OA) and rheumatoid arthritis (RA). This review also highlights new approaches to developing injectable hydrogels as delivery systems for OA and RA.
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The rapidly developing field of artificial intelligence (AI) may soon equip clinicians with algorithms that model and predict perioperative problems with extreme accuracy. Here, we outline emerging AI applications in preoperative risk stratification and intraoperative event prediction, where algorithm performance has been shown to outstrip commonly used conventional risk prediction tools. While offering an enticing view of a novel perioperative practice with superhuman foresight, AI's limited scope and lack of transparency remain key challenges for widespread adoption. As yet it is unclear whether machine learning alone can influence human clinical practice to exert real-world effects on patient outcomes.
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Aims/Background: The coronavirus disease 2019 (COVID-19) pandemic has highlighted the need for accurate and efficient diagnostic methods. This study aims to improve COVID-19 detection by integrating chest X-ray (CXR) and computerized tomography (CT) images using deep learning techniques, further improving diagnostic accuracy by using a combined imaging approach. Methods: The study used two publicly accessible databases, COVID-19 Questionnaires for Understanding the Exposure (COVID-QU-Ex) and Integrated Clinical and Translational Cancer Foundation (iCTCF), containing CXR and CT images, respectively. ⋯ The EfficientNet-based models, with their superior feature extraction capabilities, show better performance than ResNet models. Grad-CAM Visualizations provide insights into the model's decision-making process, potentially reducing diagnostic errors and accelerating diagnosis processes. This approach can improve patient care and support healthcare systems in managing the pandemic more effectively.
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Aims/Background Backward walking is gaining traction in rehabilitation therapy, showing promise as an intervention for stroke patients with walking difficulties. However, the brain activity patterns (neurophysiological mechanisms) underlying backward walking in these patients remain unclear. This study investigated the neurophysiological mechanism in stroke patients within 1 year of their stroke. ⋯ Additionally, the DAR was significantly lower during backward walking than during forward walking (p < 0.05). Conclusion This study suggests that backward walking may more effectively activate neural activity in the prefrontal and right posterior parietal cortices. This finding supports the potential of backward walking to enhance motor execution and walking function in stroke patients, thereby supporting its application as a rehabilitation method.