RESUMEN
Heart failure (HF) patients frequently present with comorbidities such as atrial fibrillation (AF) or other cardiovascular conditions, elevating their risk of thromboembolic events. Consequently, anticoagulation therapy is often considered for thromboprophylaxis, although its initiation in HF patients is complicated by concomitant bleeding risk factors. This review explores the paradoxical relationship between HF, increased bleeding risk, and the potential benefits of anticoagulation. Through an examination of existing evidence from clinical trials, observational studies, and meta-analyses, we aim to elucidate the role of anticoagulation in HF patients with increased bleeding risk. Despite guidelines recommending anticoagulation for certain HF patients with AF or other thromboembolic risk factors, uncertainty persists regarding the optimal management strategy for those at heightened risk of bleeding. The review discusses the pathophysiological mechanisms linking HF and thrombosis, challenges in bleeding risk assessment, and strategies to minimize bleeding risk while optimizing thromboprophylaxis. Shared decision-making between clinicians and patients is emphasized as essential for individualized treatment plans that balance the potential benefits of anticoagulation against the risk of bleeding complications. Furthermore, it examines emerging anticoagulant agents and their potential role in HF management, highlighting the need for further research to delineate optimal management strategies and inform evidence-based practice. In conclusion, while anticoagulation holds promise for improving outcomes in HF patients, careful consideration of patient-specific factors and ongoing research efforts are essential to optimize therapeutic strategies in this population.
RESUMEN
The gut-brain axis (GBA) is a two-way communication system that is influenced by signals from the nervous system, hormones, metabolism, the immune system, and microbes. The GBA may play a key role in gastrointestinal and neurological illnesses. Signaling events from the gut can regulate brain function. As a result, mounting data point to a connection between autoimmune disorders (AIDs), both neuroinflammatory and neurodegenerative diseases, and the GBA. Clinical, epidemiological, and experimental studies have shown that a variety of neurological illnesses are linked to alterations in the intestinal environment, which are suggestive of disease-mediated inter-organ communication between the gut and the brain. This review's objective is to draw attention to the clinical and biological relationship between the gut and the brain, as well as the clinical importance of this relationship for AIDs, neurodegeneration, and neuroinflammation. We also discuss the dysbiosis in the gut microbiota that has been linked to various AIDs, and we make some assumptions about how dietary changes such as prebiotics and probiotics may be able to prevent or treat AIDs by restoring the composition of the gut microbiota and regulating metabolites.
RESUMEN
Apert syndrome (AS), also known as type I acrocephalosyndactyly, is a rare congenital condition characterized by craniosynostosis resulting from missense mutations in the fibroblast growth factor receptor 2 (FGFR2) gene. This comprehensive review delves into AS, covering its clinical manifestations, genetics, diagnosis, medical management, psychosocial considerations, and future research directions. AS presents with distinct features, including a brachycephalic skull, midface hypoplasia, and limb anomalies such as syndactyly. It follows an autosomal dominant inheritance pattern with mutations in the FGFR2 gene. Prenatal diagnosis is possible through advanced imaging techniques and molecular testing. The multidisciplinary approach to AS management involves surgical interventions, orthodontics, and psychological support. Although no curative treatment exists, early interventions can significantly improve function and aesthetics. The quality of life for AS patients is influenced by psychosocial factors, necessitating comprehensive support for both patients and their families. Future research directions include gene therapy, understanding cellular responses to FGFR2 mutations, and addressing genetic heterogeneity. Collaborative efforts are vital to advancing knowledge about AS and its genetic underpinnings. Overall, this review serves as a valuable resource for healthcare professionals, educators, and researchers, contributing to a deeper understanding of AS and facilitating advancements in diagnosis and treatment.
RESUMEN
Rare genetic disorders (RDs), characterized by their low prevalence and diagnostic complexities, present significant challenges to healthcare systems. This article explores the transformative impact of artificial intelligence (AI) and machine learning (ML) in addressing these challenges. It emphasizes the need for accurate and early diagnosis of RDs, often hindered by genetic and clinical heterogeneity. This article discusses how AI and ML are reshaping healthcare, providing examples of their effectiveness in disease diagnosis, prognosis, image analysis, and drug repurposing. It highlights AI's ability to efficiently analyze extensive datasets and expedite diagnosis, showcasing case studies like Face2Gene. Furthermore, the article explores how AI tailors treatment plans for RDs, leveraging ML and deep learning (DL) to create personalized therapeutic regimens. It emphasizes AI's role in drug discovery, including the identification of potential candidates for rare disease treatments. Challenges and limitations related to AI in healthcare, including ethical, legal, technical, and human aspects, are addressed. This article underscores the importance of data ethics, privacy, and algorithmic fairness, as well as the need for standardized evaluation techniques and transparency in AI research. It highlights second-generation AI systems that prioritize patient-centric care, efficient patient recruitment for clinical trials, and the significance of high-quality data. The integration of AI with telemedicine, the growth of health databases, and the potential for personalized therapeutic recommendations are identified as promising directions for the field. In summary, this article provides a comprehensive exploration of how AI and ML are revolutionizing the diagnosis and treatment of RDs, addressing challenges while considering ethical implications in this rapidly evolving healthcare landscape.
