Like many developing countries, Serbia is facing a growing burden of chronic diseases. Within such public health issue, multi-morbidity requires a special attention. This study investigated the prevalence of multi-morbidity in the Serbia population and assessed the co-occurrence of chronic diseases by age and gender. We analyzed data from the 2013 National Health Survey, which included 13,103 individuals ≥ 20 years old. Multi-morbidity patterns were identified by exploratory factor analysis of data on self-reported chronic diseases, as well as data on measured body weight and height. The analysis was stratified by age and gender. Multi-morbidity was present in nearly one-third of respondents (26.9%) and existed in all age groups, with the highest prevalence among individuals aged 65 years and older (47.2% of men and 65.0% of women). Six patterns of multi-morbidity were identified: non-communicable, cardio-metabolic, respiratory, cardiovascular, aggregate, and mechanical/mental/metabolic. The non-communicable pattern was observed in both genders but only in the 20–44 years age group, while the aggregate pattern occurred only in middle-aged men. Cardio-metabolic and respiratory patterns were present in all age groups. Cardiovascular and mechanical/mental/metabolic patterns showed similar presentation in both men and women. Multi-morbidity is a common occurrence among adults in Serbia, especially in the elderly. While several patterns may be explained by underlying pathophysiologies, some require further investigation and follow-up. Recognizing the complexity of multi-morbidity in Serbia is of great importance from both clinical and preventive perspectives given that it affects one-third of the population and may require adjustment of the healthcare system to address the needs of affected individuals.

Prolonged grief disorder, also known as post-loss grief, was officially recognized in the International Classification of Diseases (ICD-11) after years of debate within the mental health community. However, while post-loss grief gained recognition, anticipatory and preparatory grief, which occur before a loss, have remained underexplored. Preparatory grief affects individuals nearing the end of life, while anticipatory grief impacts the loved ones of those who are about to die. These grief types are particularly prevalent among women, who are more vulnerable to their emotional and psychological challenges. The primary aim of this study was to investigate preparatory grief in women diagnosed with cancer and anticipatory grief in their loved ones, with the goal of developing management guidelines. The secondary objective was to identify protective factors, such as psychotherapeutic interventions and systemic support, to alleviate grief-related distress. This review synthesized evidence from the PubMed and Cochrane databases, covering studies from 1968 to 2020 and after the COVID-19 pandemic in 2023. The results revealed that anticipatory grief was common among loved ones, leading to increased emotional distress, while cancer patients experienced preparatory grief, facing both emotional and practical challenges. Both types of grief were associated with altered stress responses, such as lower diurnal cortisol levels. Psychotherapeutic interventions, particularly early and systemic psychotherapy, were found to effectively reduce symptoms of both anticipatory and preparatory grief, improving coping strategies and emotional well-being. The study concluded that empowering coping strategies and social support played key roles in enhancing emotional outcomes for both patients and their families.

Neuropsychiatric disorders are complex conditions with multifactorial etiologies, in which genetics play a pivotal role. Despite significant advancements in psychiatric research, traditional treatment options remain largely symptomatic, focusing on clinical signs without fully addressing the underlying biological causes. However, recent developments in precision medicine—an approach that tailors treatments based on genetic, environmental, and lifestyle factors—hold great promise for transforming the treatment of these disorders. By identifying specific genetic markers and understanding gene–environment interactions, precision medicine can offer more personalized and effective treatments, leading to better patient outcomes. Our primary aim was to explore how integrating genetic data with environmental factors could enhance the understanding and treatment of neuropsychiatric conditions such as schizophrenia, bipolar disorder, and depression. The secondary aim was to examine the potential of pharmacogenomics and gene therapy in improving therapeutic strategies. The results indicate that while significant progress has been made, challenges remain, including the complexity of genetic interactions and the need for more granular phenotypic data. In conclusion, precision medicine has the potential to revolutionize neuropsychiatric treatment by providing individualized care that considers genetic makeup, environmental influences, and lifestyle factors, paving the way for more effective therapies and improved patient outcomes.

Background/Objectives: Bipolar disorder (BD) is a complex and chronic mental health condition that poses significant challenges for both patients and healthcare providers. Traditional treatment methods, including medication and therapy, remain vital, but there is increasing interest in the application of artificial intelligence (AI) to enhance BD management. AI has the potential to improve mood episode prediction, personalize treatment plans, and provide real-time support, offering new opportunities for managing BD more effectively. Our primary objective was to explore the potential role of AI in transforming the management of BD, specifically in mood tracking, prediction, and personalized treatment regimens. Methods: To explore the potential role of AI in transforming BD management, we conducted a review of recent literature using key search terms. We included studies that discussed AI applications in mood tracking, prediction, and treatment personalization. The studies were selected based on their relevance to AI’s role in BD management, with attention to the PICO criteria: Population—individuals diagnosed with BD; Intervention—AI tools for mood prediction, treatment personalization, and real-time support; Comparison—traditional treatment methods (when available); Outcome—measures of mood episode prediction, treatment effectiveness, and improvements in patient care. Results: The findings from recent research reveal promising developments in the use of AI for BD management. Studies suggest that AI-powered tools can enable more proactive and personalized care, improving treatment outcomes and reducing the burden on healthcare professionals. AI’s ability to analyze data from wearable devices, smartphones, and even social media platforms provides valuable insights for early detection and more dynamic treatment adjustments. Conclusions: While AI’s application in BD management is still in its early stages, it presents transformative potential for improving patient care. However, further research and development are crucial to fully realize AI’s potential in supporting BD patients and optimizing treatment efficacy.

Data from developing countries on the rates of kidney disease are scarce. The study aimed to estimate population-based prevalence of self-reported kidney disease (SRKD) in Serbia, describe co-occurrence of chronic diseases/conditions/functional limitations in respondents with SRKD and explore association between SRKD and possible risk factors. We performed a secondary analysis of 2013 National Health Survey data. Data on a total of 14,587 respondents aged 15 years or older were analyzed using means of descriptive statistics, principal component analysis and logistic regression analysis. Out of all study respondents, 5.6% (95%CI 5.2–6.0) reported presence of kidney disease. Prevalence of all analyzed morbidities and functional limitations was higher in respondents with SRKD, and they had 8 times higher likelihood of being diagnosed with cirrhosis, 6.3 times higher likelihood of being diagnosed with urinary incontinence, more than 3 times higher likelihood of being diagnosed with degenerative disorder of bone and joint system. For cardiovascular diseases we obtained odds ratios (ORs) from 2.27 (95%CI 2.32–3.44) for heart attack to 2.95 (95%CI 2.43–3.57) for coronary heart disease. Number of co-occurrence patterns of kidney and other chronic diseases/conditions varied depending on inclusion of obesity in models. Logistic regression analysis showed that age explained most part of variability in the prevalence of SRKD and in the prevalence of two morbidities in respondents with SRKD, whereas the presence of three or more morbidities were associated with female gender, aging and low education level. Our study provided evidence that the presence of kidney disease was significantly associated with socio-demographic, lifestyle characteristics and a number of morbidities in Serbia. There is a need for integrated care and public health interventions, tackling management of NCDs and their risk factors. Detailed well-designed studies, as part of cost-effective preventive approach, are needed for chronic kidney disease screening.