Background and objective: Low back pain (LBP) is most common pain syndrome in Europe, affecting approximately 50% of European citizens. LBP is a complex condition that negatively affects many aspects of an individual’s life such as work productivity, mobility, and mental health. The aim of this study is to assess the impact of pain associated with chronic LBP on patients’ quality of life. Methods: Clinical studies reviewed in our search with no time restrictions were identified from PubMed, Web of Science, Scopus, and Cochrane Library databases. Of the initial 1929 studies, only 15 met inclusion criteria. Results: Results of our study indicate that chronic pain has a negative impact on numerous functions and areas in which the individual is involved and that this condition leads to reduced performance. Conclusions: LBP is a debilitating condition for patients, negatively affecting quality of life. Future studies should focus on validating a standardized assessment that examines all aspects affected by LBP through a customized questionnaire.

Background and Objectives: Higher level of aggression and antisocial behavior have been found in the period following head trauma. These changes are attributable to specific brain alterations that generally involved frontal lobe, insula and limbic system. A descriptive review was conducted on the specificity of aggressive behavior in relation to traumatic brain injury by evaluating numerous variables, focusing on age at the time of trauma and neuroimaging studies. Materials and Methods: We searched on PubMed and the Web of Science databases to screen references of included studies and review articles for additional citations. From an initial 738 publications, only 27 met the search criteria of describing the relationship between aggression, brain alterations and traumatic brain injury. Results: These findings showed that traumatic brain injury (TBI) is related to changes in behavior, personality and mood. Conclusions: The development of aggressive and criminal behavior is associated with multiple factors, including the etiology of injury, environmental, psychosocial and personality factors and age at the time of trauma.

Heart failure (HF) is a growing epidemic, affecting millions of people worldwide, and is a major cause of mortality, morbidity, and impaired quality of life. Traditional cardiac rehabilitation is a valuable approach to the physical and quality-of-life recovery of patients with cardiovascular disease. The innovative approach of remote monitoring through telemedicine offers a solution based on modern technologies, enabling continuous collection of health data outside the hospital environment. Remote monitoring devices present challenges that could adversely affect patient adherence, resulting in the risk of dropout. By applying a cognitive-behavioral model, we aim to identify the antecedents of dropout behavior among patients adhering to traditional cardiac rehabilitation programs and remote monitoring in order to improve the latter. Our study was conducted from October 2023 to January 2024. In the first stage, we used data from literature consultation. Subsequently, data were collected from the direct experience of 49 health workers related to both remote monitoring and traditional treatment, recruited from the authors’ workplace. Results indicate that patients with cardiovascular disease tend to abandon remote monitoring programs more frequently than traditional cardiac rehabilitation therapies. It is critical to design approaches that take these barriers into account to improve adherence and patient satisfaction. This analysis identified specific antecedents to address, helping to improve current monitoring models. This is crucial to promote care continuity and to achieve self-management by patients in the future.

Cardiovascular and neurological diseases are a major cause of mortality and morbidity worldwide. Such diseases require careful monitoring to effectively manage their progression. Artificial intelligence (AI) offers valuable tools for this purpose through its ability to analyse data and identify predictive patterns. This review evaluated the application of AI in cardiac and neurological diseases for their clinical impact on the general population. We reviewed studies on the application of AI in the neurological and cardiological fields. Our search was performed on the PubMed, Web of Science, Embase and Cochrane library databases. Of the initial 5862 studies, 23 studies met the inclusion criteria. The studies showed that the most commonly used algorithms in these clinical fields are Random Forest and Artificial Neural Network, followed by logistic regression and Support-Vector Machines. In addition, an ECG-AI algorithm based on convolutional neural networks has been developed and has been widely used in several studies for the detection of atrial fibrillation with good accuracy. AI has great potential to support physicians in interpretation, diagnosis, risk assessment and disease management.

Background and Objectives: The connection between cognitive decline and autonomy represents a complex and multifactorial area of research. Cognitive decline manifests as a progressive impairment of higher mental functions and is typical of neurodegenerative conditions such as dementia. Autonomy, on the other hand, is defined as an individual’s ability to independently manage activities of daily living and make informed decisions. The objective of this study was to investigate whether certain daily living skills can persist despite the advancement of dementia, and what factors contribute to their preservation in maintaining autonomy. Materials and Methods: A literature review was conducted using the databases PubMed, Web of Science, Scopus, Cochrane Library, Embase, and PsycInfo. Out of an initial pool of 12,113 studies, only 19 met the inclusion criteria and were selected for analysis. Results: The findings indicate that, in non-institutionalized settings, some daily living abilities may remain preserved despite cognitive deterioration. In contrast, within institutionalized environments, a significant correlation emerged between cognitive decline and the progressive loss of personal autonomy. Conclusions: This study highlights the importance of assessing residual abilities in individuals with dementia. Recognizing and supporting these remaining skills can play a crucial role in enhancing quality of life, delaying institutionalization, and promoting autonomy even in the presence of advanced cognitive decline.