Association Between Hypothyroidism and Depression in Individuals with Down Syndrome: A Retrospective Analysis.

: Down syndrome (DS) is a genetic disorder characterized by an extra copy of chromosome 21, often leading to intellectual disabilities, developmental delays, and an increased risk of various comorbidities, including thyroid dysfunction and mental health disorders. The relationship between thyroid dysfunction and mood disorders, particularly depression in DS populations, requires further investigation. : This study aims to investigate the presence of a correlative relationship between hypothyroidism and depression in 178,840 individuals with DS, utilizing data from the National Inpatient Sample (NIS) to determine if those with comorbid hypothyroidism exhibit higher rates of depression compared to their counterparts without hypothyroidism.

Racial and Sex Disparities in US Kidney Transplant Clinical Trials: A Comparative Analysis With National Transplant Registry Data.

Introduction: Chronic kidney disease and kidney failure disproportionately affect racial and ethnic minorities in the United States, yet these populations remain underrepresented in clinical trials, especially in kidney transplantation research. The objective of this study was to analyze the representation of racial, ethnic, and sex groups in US-based kidney transplant clinical trials and assess whether participant demographics reflect the population receiving transplants, using national registry data.

Methods: A total of 188 completed interventional trials related to kidney transplantation (1995-2022) were extracted from clinicaltrials.

Comprehensive Approaches to Pain Management in Postoperative Spinal Surgery Patients: Advanced Strategies and Future Directions.

Effective postoperative pain management remains a major clinical challenge in spinal surgery, with poorly controlled pain affecting up to 50% of patients and contributing to delayed mobilization, prolonged hospitalization, and risk of chronic postsurgical pain. This review synthesizes current and emerging strategies in postoperative spinal pain management, tracing the evolution from opioid-centric paradigms to individualized, multimodal approaches. Multimodal analgesia (MMA) has become the cornerstone of contemporary care, combining pharmacologic agents, such as non-steroidal anti-inflammatory drugs (NSAIDs), acetaminophen, and gabapentinoids, with regional anesthesia techniques, including erector spinae plane blocks and liposomal bupivacaine.

Emerging Therapies for Neurological Disorders: A Clinical Review of MANAGED (Music, Art, Nature-Based, Animal-Assisted, Game, Essential Oil, Dance) Care.

In the face of the limitations in pharmacological and surgical interventions for neurological conditions such as Parkinson's and Alzheimer's disease, patients are increasingly turning to non-pharmacological and alternative therapies to manage their symptoms and improve their quality of life. This shift underscores the urgent need for accessible, effective, and affordable treatments. This literature review examines a range of alternative and personalized therapies, including game therapy, animal-assisted therapy, dance therapy, art therapy, music therapy, aroma therapy, and shinrin-yoku therapy.

American Epilepsy Society/International League Against Epilepsy-North America Joint Task Force for Epilepsy Health Care Disparities in the United States.

Numerous factors including social determinants of health, knowledge gaps, economic challenges, workforce limitations, and health system deficiencies are associated with significant disparities in access to health care services and health outcomes for people with epilepsy (PWE). The American Epilepsy Society (AES) and the International League Against Epilepsy-North America (ILAE-NA) established a joint task force to explore and develop recommendations to address health care disparities experienced by PWE. The task force gathered foundational knowledge through meetings, public and patient organization comments and discussions to develop consensus recommendations.

Strategies to Reduce Hospital Length of Stay: Evidence and Challenges.

Hospital length of stay (HLOS) is a critical healthcare metric influencing patient outcomes, resource utilization, and healthcare costs. While reducing HLOS can improve hospital efficiency and patient throughput, it also poses risks such as premature discharge, increased readmission rates, and potential compromise of patient safety. This literature review synthesizes current evidence on the determinants of HLOS, including patient-specific factors such as demographics, comorbidities, and socioeconomic status, as well as hospital-related factors like admission route, resource allocation, and institutional policies.

Artificial Intelligence Advancements in Oncology: A Review of Current Trends and Future Directions.

Cancer remains one of the leading causes of mortality worldwide, driving the need for innovative approaches in research and treatment. Artificial intelligence (AI) has emerged as a powerful tool in oncology, with the potential to revolutionize cancer diagnosis, treatment, and management. This paper reviews recent advancements in AI applications within cancer research, focusing on early detection through computer-aided diagnosis, personalized treatment strategies, and drug discovery.

Prediction of Mortality After Convulsive Status Epilepticus: The Status Epilepticus MASH Score.

PurposeThis study aimed to investigate in-patient mortality and predictors of death associated with convulsive status epilepticus (CSE) in a large nationwide cohort and create a simplified predictive score for in-hospital mortality.MethodsRetrospective data from the National Inpatient Sample (NIS) database between 2007 and 2014 were analyzed, including 123,082 adults with CSE. Univariate logistic testing identified admission variables, neurological and medical complications associated with mortality.

Traumatic Brain Injury and Artificial Intelligence: Shaping the Future of Neurorehabilitation-A Review.

Traumatic brain injury (TBI) is a leading cause of disability and death globally, presenting significant challenges for diagnosis, prognosis, and treatment. As healthcare technology advances, artificial intelligence (AI) has emerged as a promising tool in enhancing TBI rehabilitation outcomes. This literature review explores the current and potential applications of AI in TBI management, focusing on AI's role in diagnostic tools, neuroimaging, prognostic modeling, and rehabilitation programs.

Cerebrovascular Health Among Sex- and Gender-Diverse People: A Narrative Review.

Purpose Of Review: Sex and gender diversity includes people who are intersex, transgender, and nonbinary. Americans are identifying as sex and gender diverse (SGD) in increasing numbers. Although data are limited on the diagnosis and management of stroke in SGD communities, the current literature suggests that there may be unique health needs among these marginalized populations.

The Role of Artificial Intelligence in Obesity Risk Prediction and Management: Approaches, Insights, and Recommendations.

Greater than 650 million individuals worldwide are categorized as obese, which is associated with significant health, economic, and social challenges. Given its overlap with leading comorbidities such as heart disease, innovative solutions are necessary to improve risk prediction and management strategies. In recent years, artificial intelligence (AI) and machine learning (ML) have emerged as powerful tools in healthcare, offering novel approaches to chronic disease prevention.

Exploring cardiopulmonary rehabilitation in the middle east and North Africa region: A narrative review of challenges and opportunities.

Background And Objectives: Cardiopulmonary Rehabilitation (CR) is crucial for managing conditions like congestive heart failure (CHF), chronic obstructive pulmonary disease (COPD), and post-COVID-19 complications. This review examines CR practices in the Middle East and North Africa (MENA) region, exploring challenges, disparities, and emerging trends.

Methods: A comprehensive literature search was conducted in PubMed, Scopus, and Web of Science to identify studies published between date of inception and April 24th, 2024, focusing on CR programs, outcomes, challenges, and strategies specific to the MENA region.

Digital pathology, deep learning, and cancer: a narrative review.

Background And Objective: Cancer is a leading cause of morbidity and mortality worldwide. The emergence of digital pathology and deep learning technologies signifies a transformative era in healthcare. These technologies can enhance cancer detection, streamline operations, and bolster patient care.