Prevalence of mental health disorders in knee osteoarthritis patients: a systematic review and meta-analysis.

Background: Knee osteoarthritis (OA) is a prevalent degenerative disease affecting synovial joints, predominantly the knee, leading to various complications, including mental health conditions like depression and anxiety. This systematic review aimed to determine the prevalence of depression and anxiety in knee OA patients. Methods: A comprehensive literature search was conducted in various databases till September 15, 2023. Studies focusing on the prevalence of mental health issues in patients with knee OA were included, excluding narrative reviews, protocols, unpublished reports, editorials, case reports, abstracts, and commentaries. All statistical analyses were performed in R version 4.2.3. Results: This review included a total of 14 studies involving middle-aged to elderly adult patients with knee OA, with ages ranging from 45 to 75 years. Among these, 13 studies involving 3390 adult patients with an average age of 59.75 years reported a pooled prevalence of depression of 30% (95% confidence interval: 18-43), demonstrating a substantial heterogeneity (I 2=98%). Additionally, anxiety was identified with a combined prevalence of 27% (95% confidence interval: 24-30) based on three studies that included 1407 older adult patients with an average age of 62.1 years. These studies displayed minimal heterogeneity (I 2=7%). Conclusion: The findings show a significant prevalence of depression among adult patients with knee OA and anxiety among older adults with knee OA, emphasizing the need for integrated healthcare approaches that address both orthopedic and mental health conditions. More comprehensive research is essential to deepen our understanding of the connection between mental illnesses and knee OA and to develop effective preventive and treatment strategies.

Exploring Health Informatics in the Battle against Drug Addiction: Digital Solutions for the Rising Concern.

Drug addiction is a rising concern globally that has deeply attracted the attention of the healthcare sector. The United States is not an exception, and the drug addiction crisis there is even more serious, with 10% of adults having faced substance use disorder, while around 75% of this number has been reported as not having received any treatment. Surprisingly, there are annually over 70,000 deaths reported as being due to drug overdose. Researchers are continually searching for solutions, as the current strategies have been ineffective. Health informatics platforms like electronic health records, telemedicine, and the clinical decision support system have great potential in tracking the healthcare data of patients on an individual basis and provide precise medical support in a private space. Such technologies have been found to be useful in identifying the risk factors of drug addiction among people and mitigating them. Moreover, the platforms can be used to check prescriptions of addictive drugs such as opioids and caution healthcare providers. Programs such as the Prescription Drug Monitoring Program (PDMP) and the Drug and Alcohol Services Information Systems (DASIS) are already in action in the US, but the situation demands more in-depth studies in order to mitigate substance use disorders. Artificial intelligence (AI), when combined with health informatics, can aid in the analysis of large amounts of patient data and aid in classifying nature of addiction to assist in the provision of personalized care.

Unveiling New Strategies Facilitating the Implementation of Artificial Intelligence in Neuroimaging for the Early Detection of Alzheimer's Disease.

Alzheimer's disease (AD) is a chronic neurodegenerative disorder with a global impact. The past few decades have witnessed significant strides in comprehending the underlying pathophysiological mechanisms and developing diagnostic methodologies for AD, such as neuroimaging approaches. Neuroimaging techniques, including positron emission tomography and magnetic resonance imaging, have revolutionized the field by providing valuable insights into the structural and functional alterations in the brains of individuals with AD. These imaging modalities enable the detection of early biomarkers such as amyloid-ß plaques and tau protein tangles, facilitating early and precise diagnosis. Furthermore, the emerging technologies encompassing blood-based biomarkers and neurochemical profiling exhibit promising results in the identification of specific molecular signatures for AD. The integration of machine learning algorithms and artificial intelligence has enhanced the predictive capacity of these diagnostic tools when analyzing complex datasets. In this review article, we will highlight not only some of the most used diagnostic imaging approaches in neurodegeneration research but focus much more on new tools like artificial intelligence, emphasizing their application in the realm of AD. These advancements hold immense potential for early detection and intervention, thereby paving the way for personalized therapeutic strategies and ultimately augmenting the quality of life for individuals affected by AD.

Incidence of Post-operative Gastro-esophageal Reflux Disorder in Patients Undergoing Laparoscopic Sleeve Gastrectomy: A Systematic Review and Meta-analysis.

Gastroesophageal reflux disease (GERD) is a common concern following laparoscopic sleeve gastrectomy (LSG). This paper aimed to assess the incidence of reflux disease following these bariatric procedures. A literature search was conducted to identify observational studies and clinical trials reporting patients developed GERD disease after LSG. Twenty-two studies included in the analysis, involve 20,495 participants, indicated that the estimated proportion of patients who developed post-surgery GERD was 0.35 (95% CI 0.30-0.41). Subgroup analysis revealed a proportion of 0.33 (95% CI 0.27-0.38) in observational studies and 0.58 (95% CI 0.39-0.75) in clinical trials. High heterogeneity was noted across studies (I2 = 98%). Sensitivity analyses and publication bias assessments were performed to enhance the robustness of the results. Our findings highlight a moderate to high risk of developing GERD following LSG surgery.

Sensory Integration: A Novel Approach for Healthy Ageing and Dementia Management.

Sensory processing is a fundamental aspect of the nervous system that plays a pivotal role in the cognitive decline observed in older individuals with dementia. The "sensory diet", derived from sensory integration theory, may provide a tailored approach to modulating sensory experiences and triggering neuroplastic changes in the brain in individuals with dementia. Therefore, this review aimed to investigate the current knowledge regarding the sensory diet and its potential application to dementia. This review encompassed an extensive search across multiple databases, including PubMed, Google Scholar, covering articles published from 2010 to 2023. Keywords such as "sensory integration", "sensory modulation", "healthy aging", and "dementia" were utilized to identify relevant studies. The types of materials retrieved included peer-reviewed articles, systematic reviews, and meta-analyses, ensuring a comprehensive overview of the current research landscape. This article offers a comprehensive exploration of the effectiveness of sensory diets such as tactile stimulation, auditory therapies, and visual interventions, which have demonstrated noteworthy efficacy in addressing challenges linked to aging and dementia. Research findings consistently report positive outcomes, such as improved cognitive function, elevated emotional well-being, and enhanced overall quality of life in older individuals. Furthermore, we found that the integration of sensory diets with the metaverse, augmented reality, and virtual reality opens up personalized experiences, fostering cognitive stimulation and emotional well-being for individuals during aging. Therefore, we conclude that customized sensory diets, based on interdisciplinary cooperation and leveraging technological advancements, are effective in optimizing sensory processing and improve the overall well-being of older individuals contending with sensory modulation challenges and dementia.