Annals of medicine
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Randomized Controlled Trial Multicenter Study
A multicenter feasibility randomized controlled trial using a virtual reality application of pain neuroscience education for adults with chronic low back pain.
Chronic low back pain (CLBP) is a highly prevalent condition among adults and is correlated to high levels of pain, high disability, and lower quality of life. Pain neuroscience education (PNE) helps to explain the pain experience and can affect psychosocial factors, such as fear of movement, anxiety, socioeconomic status, work life satisfaction, etc. More recently, virtual reality (VR) programs have emerged allowing for immersive PNE experiences. ⋯ The results of the trial suggest that VR-PNE may be acceptable and feasible for patients with CLBP. Study procedures and PT delivery modifications should be considered for the next iteration of this study to improve follow-up assessment rates.
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Review
Outpatient management of essential hypertension: a review based on the latest clinical guidelines.
Background: Essential hypertension, a prevalent cardiovascular condition, poses a significant health burden worldwide. Based on the latest American clinical guidelines, half of adults in the United States have hypertension. Of these, only about a half are treated and about a quarter are adequately controlled for hypertension. ⋯ Notably, it emphasizes the importance of individualized treatment plans tailored to patients' specific risk profiles and comorbidities. Results: By consolidating the latest advancements in hypertension management, this review provides clinicians with an up-to-date reference, offering a nuanced understanding of treatment goals and strategies. Conclusion: Through the incorporation of evidence-based recommendations, healthcare practitioners can optimize patient care, mitigate potential complications, and improve overall outcomes in essential hypertension.
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Despite the widespread administration of coronavirus disease 2019 (COVID-19) vaccines, the impact on patients with asymptomatic to mild illness remains unclear. Here, we aimed to assess the efficacy of various vaccine doses and types on the duration of isolation duration and discharge rates, the viral shedding duration, and negative rates in asymptomatic to mild COVID-19 patients. ⋯ Full vaccination was effective, with heterologous vaccines showing greater efficacy than inactivated vaccines alone. However, there was no significant difference in the vaccine protective effect 12 months after vaccination.
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Fibrosis is a pathological process that occurs due to chronic inflammation, leading to the proliferation of fibroblasts and the excessive deposition of extracellular matrix (ECM). The process of long-term fibrosis initiates with tissue hypofunction and progressively culminates in the ultimate manifestation of organ failure. Intestinal fibrosis is a significant complication of Crohn's disease (CD) that can result in persistent luminal narrowing and strictures, which are difficult to reverse. ⋯ Molecular imaging has the potential to be employed for early detection, disease staging, and prognostication in addition to assessing disease activity and treatment response in IBD. Molecular imaging methods also have a potential role to enabling minimally invasive assessment of intestinal fibrosis. This review discusses the role of molecular imaging in combination of AI in detecting CD fibrosis.
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Infectious diseases are a major threat for human and animal health worldwide. Artificial Intelligence (AI) combined algorithms including Machine Learning and Big Data analytics have emerged as a potential solution to analyse diverse datasets and face challenges posed by infectious diseases. In this commentary we explore the potential applications and limitations of ML to management of infectious disease. ⋯ We propose potential solutions to mitigate these hurdles and applications of ML to identify biomolecules for effective treatment and prevention of infectious diseases. In addition to use of ML for management of infectious diseases, potential applications are based on catastrophic evolution events for the identification of biomolecular targets to reduce risks for infectious diseases and vaccinomics for discovery and characterization of vaccine protective antigens using intelligent Big Data analytics techniques. These considerations set a foundation for developing effective strategies for managing infectious diseases in the future.