Rev Invest Clin
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Observational Study
Assessment of Osteoprotegerin and Receptor Activator of Nf-Κb Ligand in Malaysian Male Patients with Chronic Obstructive Pulmonary Disease: A Cross-Sectional Study.
Background: Limited information exists regarding the pathophysiological interactions between osteoporosis and chronic obstructive pulmonary disease (COPD). Objective: To study the association of Osteoprotegerin (OPG) and receptor activator of nuclear factor kappa-Β ligand (RANKL) in male COPD patients. Methods: An observational clinical study was conducted at Penang General Hospital in Malaysia. ⋯ Furthermore, patients with severe COPD had a 3 times greater risk of developing osteoporosis (OR = 2.997 [95% CI = 2.181, 4.118], p < 0.001), while spirometric parameters had a significant inverse relationship with osteoporosis (FEV1% OR = 0.970, [95% CI = 0.954, 0.986], p = 0.001; FEV1/FVC OR = 0.984, (95% CI = 0.970, 0.999], p = 0.035). Conclusion: The study concluded that COPD patients had lower sOPG levels, leading to decreased OPG/RANKL ratio and faster bone resorption. Low bone mineral density was associated with more severe COPD. (Rev Invest Clin. 2024;76(6):262-73).
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Background: COVID-19 is a disease that had a great impact in the world, generating lifestyle changes; among these are changes in sleep quality, with the elderly being one of the most affected age groups. Objective: To identify sleep alterations in Mexican people older than 60 years post COVID-19 pandemic. Methods: We performed a descriptive study on subjects older than 60 years from the aging cohort of the National Institute of Respiratory Diseases. ⋯ In the questionnaire on toxicology, we found higher alcohol consumption (18% vs. 27%, p = 0.01) and vitamin ingestion (34% vs. 46%, p = 0.003). Subjects also described more nighttime awakenings, with more than 3 times per week (25% vs. 44%, p < 0.0001), generating a worse auto perception of healthy well-being (88.3 vs. 82.02 p < 0.0001). Conclusions: The COVID-19 pandemic affected sleep quality in different aspects, and it increased the consumption of alcohol and vitamins. (Rev Invest Clin. 2024;76(6):239-42).
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Background: The effective use of combination antiretroviral therapy (ART) has significantly improved the life expectancy of people living with the human immunodeficiency virus (HIV). However, complications have shifted from opportunistic infections to issues such as drug toxicity and resistance, as well as an increase in premature cardiovascular diseases (CVD). These conditions are attributed to chronic immune activation and persistent inflammation caused by HIV, along with lipid abnormalities and insulin resistance. ⋯ In addition, 53.8% of the patients exhibited hypertriglyceridemia, and 54.8% met the diagnostic criteria for metabolic syndrome. The D: A: D reduced and full models identified significant risk factors for individuals over 30 years of age, highlighting notable associations with cholesterol levels, triglyceride levels, and smoking status. In contrast, the Framingham model did not demonstrate significant risk associations. (Rev Invest Clin. 2024;76(6):274-85).
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Artificial intelligence (AI) generative models driven by the integration of AI and natural language processing technologies, such as OpenAI's chatbot generative pre-trained transformer large language model (LLM), are receiving much public attention and have the potential to transform personalized medicine. Dialysis patients are highly dependent on technology and their treatment generates a challenging large volume of data that has to be analyzed for knowledge extraction. We argue that, by integrating the data acquired from hemodialysis treatments with the powerful conversational capabilities of LLMs, nephrologists could personalize treatments adapted to patients' lifestyles and preferences. ⋯ In this paper, we will revise LLMs potential strengths in terms of their contribution to personalized medicine, and, in particular, their potential impact, and limitations in nephrology. Nephrologists' collaboration with AI academia and companies, to develop algorithms and models that are more transparent, understandable, and trustworthy, will be crucial for the next generation of dialysis patients. The combination of technology, patient-specific data, and AI should contribute to create a more personalized and interactive dialysis process, improving patients' quality of life.
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Blood purification as an adjunctive therapy has been studied for several decades. In this review, we will focus on the most recent studies, particularly on adsorption techniques. These include hemofilters with adsorptive membranes, both endotoxin-specific and non-specific. ⋯ In the context of viruses, especially COVID-19, we require a deeper understanding of the complexities involved in viral replication, as this could significantly impact the efficacy of blood purification techniques. The failures highlighted for each device should be viewed as potential areas for improvement. Despite the challenges, we remain hopeful that these techniques will eventually succeed and prove beneficial in the future.