Background and Objectives: Artificial intelligence has emerged as a transformative tool in healthcare, offering capabilities such as early diagnosis, personalised treatment, and real-time patient monitoring. In the context of rheumatoid arthritis, a chronic autoimmune disease that demands timely intervention, artificial intelligence shows promise in overcoming diagnostic delays and optimising disease management. This study examines the role of artificial intelligence in the diagnosis and management of rheumatoid arthritis, focusing on perceived benefits, challenges, and acceptance levels among healthcare professionals and patients. Materials and Methods: A cross-sectional study was conducted using a detailed questionnaire distributed to 205 participants, including rheumatologists, general practitioners, and rheumatoid arthritis patients from Romania. The study used descriptive statistics, chi-square tests, and logistic regression to analyse AI acceptance in rheumatology. Data visualisation and multiple imputations addressed missing values, ensuring accuracy. Statistical significance was set at p < 0.05 for hypothesis testing. Results: Respondents with prior experience in artificial intelligence perceived it as more useful for early diagnosis and personalised management of RA (p < 0.001). Familiarity with artificial intelligence concepts positively correlated with acceptance in routine rheumatology practice (ρ = 1.066, p < 0.001). The main barriers identified were high costs (36%), lack of medical staff training (37%), and concerns regarding diagnostic accuracy (21%). Although less frequently mentioned, data privacy concerns remained relevant for a subset of respondents. The study revealed that artificial intelligence could improve diagnostic accuracy and rheumatoid arthritis monitoring, being perceived as a valuable tool by professionals familiar with digital technologies. However, 42% of participants cited the lack of data standardisation across medical systems as a major barrier, underscoring the need for effective interoperability solutions. Conclusions: Artificial intelligence has the potential to revolutionise rheumatoid arthritis management through faster and more accurate diagnoses, personalised treatments, and optimised monitoring. Nevertheless, challenges such as costs, staff training, and data privacy need to be addressed to ensure efficient integration into clinical practice. Educational programmes and interdisciplinary collaboration are essential to increase artificial intelligence adoption in rheumatology.

Introduction: COVID-19 infection is often associated with a vast spectrum of opportunistic bacterial and fungal infections. Herein, we share a summary of the first case of COVID-19-associated mucormycosis (CAM) in a patient from Romania. Case presentation: A 51-year-old male non-smoker, with no known relevant medical history, who denied any previous alcohol use and was vaccinated against COVID-19 (complete scheme with Vaxzevria), was admitted to the hospital for severe COVID-19 infection. The first mucormycosis-related symptoms were reported on the eighth day of admission and were followed by the rapid deterioration of the patient’s condition and, consequently, death. The main aggravating factors, which were identified to be associated with the development of mucormycosis and with the poor outcome, were the association of severe COVID-19, new-onset COVID-19-triggered type 2 diabetes, and corticoid treatment for severe COVID-19. Conclusion: The association between severe COVID-19 and newly diagnosed type 2 diabetes, triggered by COVID-19 infection, increases the risk of severe opportunistic fungal infections and the associated mortality rates.

Background: Rheumatoid arthritis (RA) is a chronic autoimmune disease characterised by systemic inflammation and the progressive damage of joints, significantly impacting patients’ quality of life. Managing this condition requires a complex approach that integrates pharmacological and non-pharmacological therapies, alongside psychosocial support and patient education. Aim: This study aims to highlight the importance of an interdisciplinary approach in the treatment of rheumatoid arthritis, focusing on the role of pharmacological therapies, monitoring treatment response, and the involvement of a multidisciplinary team in the effective management of the disease. Methods: The analysis was based on a review of the specialised literature concerning the role of disease-modifying antirheumatic drugs (DMARDs, both conventional and biological), the use of inflammatory markers (CRP and ESR), advanced imaging techniques, and the contribution of various medical specialities to the holistic management of rheumatoid arthritis. A total of 595,900 records were identified, of which 53 studies were ultimately included in the detailed analysis. Relevant studies from fields such as rheumatology, nutrition, psychology, and physical therapy were included. Results: The findings underline that DMARDs, in combination with other pharmacological therapies, remain essential for slowing disease progression. Monitoring treatment response through inflammatory markers and imaging techniques allows for the adjustment of therapeutic strategies and the prevention of complications. An interdisciplinary approach, involving the rheumatologist, general practitioner, physiotherapist, nutritionist, and psychologist, provides significant benefits, such as reducing inflammation, improving joint function, and offering psychosocial support. Conclusions: The effective management of rheumatoid arthritis requires a personalised interdisciplinary approach. Integrating various specialities, along with patient education and psychosocial support, contributes to better disease management, the prevention of disabilities, and improved quality of life. This review is not registered.

Background: Elderly patients with COVID-19 often exhibit a complex interplay between hypercoagulability and coagulopathy, key factors in determining the risk of severe complications and mortality. This study aimed to analyze coagulation and inflammatory markers to identify critical predictors of adverse outcomes in this vulnerable population. Material and Methods: The retrospective study was conducted on a sample of 1429 elderly patients (≥60 years) diagnosed with COVID-19, hospitalized in “Sf. Ap. Andrei” St. Apostle Andrew’s County Emergency Hospital in various wards between March 2020 and August 2022. Data were collected from medical records and included inflammatory markers (C-reactive protein, procalcitonin, ESR) and coagulation markers (prothrombin time, INR, fibrinogen, D-dimer). The SPSS 2.0 statistical software was used to conduct the study. Results:Coagulation markers: Prothrombin activity averaged 74.22%, below normal levels, indicating a heightened bleeding risk, while fibrinogen levels were significantly elevated (mean: 531.69 mg/dL), reflecting hypercoagulability. Prolonged prothrombin time (mean: 17.28 s) and elevated INR (International normalized ratio) (mean: 1.51) were associated with increased mortality, emphasizing their role in risk stratification. Elevated D-dimer levels (mean: 2.75 mg/L) further highlighted thromboembolic risks. Inflammatory markers: C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR) showed marked elevations (mean CRP: 92.09 mg/L, mean ESR: 58.47 mm/h), correlating with heightened systemic inflammation and poor outcomes. Bacterial infections: Elevated procalcitonin (mean: 1.98 ng/mL) suggested secondary bacterial infections, particularly in mechanically ventilated patients, significantly worsening prognosis. Conclusions: The duality of hypercoagulability and coagulopathy in elderly COVID-19 patients underscores the importance of consistently monitoring coagulation markers such as prothrombin time, INR, D-dimer, and fibrinogen. Simultaneously, elevated inflammatory markers and secondary bacterial infections require prompt therapeutic interventions. This study highlights the critical need for personalized management strategies to mitigate complications and reduce mortality in this high-risk population.

(1) Background: As dementia is an incurable, multifactorial neurodegenerative disease, we gathered and analyzed a number of patient characteristics, assessing possible correlations that may support early diagnosis and a more accurate prognosis for cognitively impaired patients. (2) Methods: We used standard clinical parameters (cognitive and functional status, comorbidities, and plasma vitamin D levels) in a study group of 162 patients aged above 55 years old. (3) Results: We reported a higher incidence of cardiovascular and metabolic comorbidities in patients with severe or moderate cognitive impairment; a validated correlation between functional status, cognitive status, and serum vitamin D levels; and a more frequently associated profile of neurologic comorbidities in patients with a more significant cognitive deficiency. (4) Conclusions: The present research adds data on the significant correlations of cognitive deficits with cardiovascular, metabolic, and neurologic diseases (and the lack of correlation with osteoarticular illness). Clinicians should make the best use of the current screening and assessment tools (such as the functional scoring of daily activities, cognitive evaluation, and the screening of risk factors). Our data may offer starting points for future in-depth analysis of dementia-modifiable risk factors.

Background. Rheumatoid arthritis (RA) is a chronic autoimmune disease frequently accompanied by cardiovascular, respiratory, skeletal, psychiatric, and neoplastic comorbidities that are associated with higher morbidity and poorer health-related quality of life (HRQoL). This study evaluated the associations between comorbidities and patient-reported physical health, emotional distress, daily functioning, and social relationships in adults with RA and explored patient-reported unmet needs relevant to integrated care. Methods. We conducted a cross-sectional survey among 286 adults with physician-confirmed RA, using a structured questionnaire (ICRA-Q) administered between June and July 2025 via online platforms and in-hospital supervised completion. The survey captured demographics, patient-reported physician-diagnosed comorbidities (current and/or past), perceived disease impact, functional limitations, emotional and social consequences, access to treatment, financial burden, and support needs. Analyses included descriptive statistics, χ² tests, t-tests/ANOVA, effect sizes (Cramer’s V and standardized mean differences), and multivariable logistic regression to explore predictors of high HRQoL impact and high difficulty in disease management. An exploratory classification into high-risk phenotypes was performed using predefined clinical, psychological, and socioeconomic criteria. Results. Most participants (98.6%) reported at least one comorbidity, most commonly hypertension, osteoporosis, and cardiovascular disease. Higher comorbidity burden and depression/anxiety were strongly associated with higher pain, reduced mobility, emotional distress, and financial strain. Exploratory high-risk phenotypes (severe somatic multimorbidity, high psychological vulnerability, high socioeconomic burden, and a composite very high-risk profile) were associated with poorer HRQoL indicators. Younger age, shorter disease duration, and higher perceived social support were associated with lower perceived burden. Conclusions. In this cross-sectional, patient-reported study, comorbidity burden—particularly psychological comorbidity—was strongly associated with poorer HRQoL and greater management difficulty in RA. These findings support the need for multidisciplinary, integrated care pathways; however, subgroup phenotypes should be considered exploratory and require external validation.