Review of psychological interventions in patients with cancer.

OBJECTIVE: Cancer is one of the leading causes of mortality in the world and also causes morbidity and deterioration in the mental health of patients and their caregivers. The most commonly reported psychological symptoms include anxiety, depression, and the fear of recurrence. The purpose of this narrative review is to elaborate and discuss the effectiveness of the different interventions employed and their utilities in clinical practice. METHODS: Scopus and PubMed databases were searched, with a timeframe from 2020 to 2022, to identify randomised controlled trials, meta-analyses, and reviews and reported using PRISMA guidelines. Articles were searched by the following keywords: "cancer, psychology, anxiety, and depression". An additional search was performed with the keywords "cancer, psychology, anxiety, depression, and [intervention name]". The most popular psychological interventions were included in these search criteria. RESULTS: A total of 4829 articles were retrieved by the first preliminary search. After reducing duplicates, 2964 articles were assessed for inclusion according to eligibility criteria. After the full-text screening, 25 final articles were chosen. To systematise psychological interventions as described in the literature, the authors have divided them into 3 broad categories, each type targeting a specific domain of mental health: cognitive-behavioural, mindfulness, and relaxation. CONCLUSION: The most efficient psychological therapies, as well as therapies which require more extensive research, were outlined in this review. The authors discuss the necessity of primary assessment of patients and whether they require the help of a specialist. With the limitations of the potential risk of bias, an overview of different therapies and interventions targeting various psychological symptoms is outlined.

Empowering health care consumers & understanding patients' perspectives on AI integration in oncology and surgery: A perspective.

Introduction: Artificial intelligence (AI) is transforming oncology and surgery by improving diagnostics, personalizing treatments, and enhancing surgical precision. Patients appreciate AI for its potential to provide accurate prognoses and tailored therapies. However, AI's implementation raises ethical concerns, data privacy issues, and the need for transparent communication between patients and health care providers. This study aims to understand patients' perspectives on AI integration in oncology and surgery to foster a balanced and patient-centered approach. Methods: The study utilized a comprehensive literature review and analysis of existing research on AI applications in oncology and surgery. The focus was on examining patient perceptions, ethical considerations, and the potential benefits and risks associated with AI integration. Data was collected from peer-reviewed journals, conference proceedings, and expert opinions to provide a broad understanding of the topic. The perspectives of patients was also emphasized to highlight the nuances of their acceptance and concerns regarding AI in their health care. Results: Patients generally perceive AI in oncology and surgery as beneficial, appreciating its potential for more accurate diagnoses, personalized treatment plans, and improved surgical outcomes. They particularly value AI's role in providing timely and precise diagnostics, which can lead to better prognoses and reduced anxiety. However, concerns about data privacy, ethical implications, and the reliability of AI systems were prevalent. Consequently, trust in AI and health care providers was deemed as a crucial factor for patient acceptance. Additionally, the need for transparent communication and ethical safeguards was also highlighted to address these concerns effectively. Conclusion: The integration of AI in oncology and surgeryholds significant promise for enhancing patient care and outcomes. Patients view AI as a valuable tool that can provide accurate prognoses and personalized treatments. However, addressing ethical concerns, ensuring data privacy, and building trust through transparent communication are essential for successful AI integration. Future initiatives should focus on refining AI algorithms, establishing robust ethical guidelines, and enhancing patient education to harmonize technological advancements with patient-centered care principles.

Beyond symptoms: Unlocking the potential of coronary calcium scoring in the prevention and treatment of coronary artery disease.

Coronary Artery Disease (CAD) represents a persistent global health menace, particularly prevalent in Eastern European nations. Often asymptomatic until its advanced stages, CAD can precipitate life-threatening events like myocardial infarction or stroke. While conventional risk factors provide some insight into CAD risk, their predictive accuracy is suboptimal. Amidst this, Coronary Calcium Scoring (CCS), facilitated by non-invasive computed tomography (CT), emerges as a superior diagnostic modality. By quantifying calcium deposits in coronary arteries, CCS serves as a robust indicator of atherosclerotic burden, thus refining risk stratification and guiding therapeutic interventions. Despite certain limitations, CCS stands as an instrumental tool in CAD management and in thwarting adverse cardiovascular incidents. This review delves into the pivotal role of CCS in CAD diagnosis and treatment, elucidates the involvement of calcium in atherosclerotic plaque formation, and outlines the principles and indications of utilizing CCS for predicting major cardiovascular events.

The impact of diabetes in cognitive impairment: A review of current evidence and prospects for future investigations.

Cognitive impairment in individuals with diabetes represents a multifaceted and increasingly prevalent health concern. This review critically examines the current evidence regarding the intricate relationship between diabetes and cognitive decline. It highlights the existing knowledge on the impact of diabetes on cognitive function, spanning from mild cognitive impairment to dementia, including vascular and Alzheimer dementia. The review underscores the need for a standardized diagnostic paradigm and explores research gaps, such as the implications of cognitive impairment in younger populations and various diabetes types. Furthermore, this review emphasizes the relevance of diabetes-related comorbidities, including hypertension and dyslipidemia, in influencing cognitive decline. It advocates for a comprehensive, interdisciplinary approach, integrating insights from neuroscience, endocrinology, and immunology to elucidate the mechanistic underpinnings of diabetes-related cognitive impairment. The second part of this review outlines prospective research directions and opportunities. It advocates for longitudinal studies to understand disease progression better and identifies critical windows of vulnerability. The search for accurate biomarkers and predictive factors is paramount, encompassing genetic and epigenetic considerations. Personalized approaches and tailored interventions are essential in addressing the substantial variability in cognitive outcomes among individuals with diabetes.