Burnout and stress-related issues are significant concerns among medical personnel involved in emergency situations due to the high demands of their work. A cross-sectional descriptive and comparative study was conducted on 266 prehospital emergency personnel across five Romanian counties, comprising 41 physicians, 74 nurses, and 151 paramedics. Data were collected through an online form, including demographic and professional characteristics, and five validated scales. This study revealed moderate (49.3%) to high (25.9%) burnout rates, with 35% showing signs of work addiction. Despite these challenges, the personnel demonstrated high levels of stress-related growth (61.2%), strong self-discipline (74.1%), and low to moderate responsive distress (100%). Physicians exhibited higher work addiction and job satisfaction, whereas paramedics faced higher burnout, self-discipline, and distress levels. Nurses showed lower burnout and self-discipline levels. These findings highlight the prevalence of burnout and work addiction among emergency medical personnel, while also underscoring the presence of protective factors like higher self-discipline, good level of stress-related growth, and low to moderate responsive distress. The distinct differences in experiences among physicians, nurses, and paramedics emphasize the need for tailored strategies to address these issues within each group.

Background/Objectives: This is a cross-sectional study designed to explore the contribution of personality factors (the Alternative Five Factor Model) and lower order characteristics (responsive distress and self-discipline) to burnout, work addiction, and stress-related growth among Romanian prehospital emergency healthcare workers. Methods: A total of 266 prehospital professionals (41 physicians, 74 nurses, and 151 paramedics) participated in the study out of the 728 invited (36.5% response rate). The age of participants ranged between 20 and 57 years and 67.3% were men. The participants completed the Oldenburg Burnout Inventory, the Dutch Work Addiction Scale (the short version), the Stress-Related Growth Scale, the Zuckerman–Kuhlman Personality Inventory, the Responsive Distress Scale, and the Self-Discipline Scale. Results: The results show that burnout was predicted by age, gender, impulsive sensation seeking, responsive distress, and self-discipline; work addiction was predicted by aggression–hostility, sociability, and responsive distress, while stress-related growth was predicted by age, activity, and self-discipline. Additionally, we found that emergency healthcare workers displayed lower impulsive sensation seeking, neuroticism–anxiety, and aggression–hostility, but displayed higher levels of activity and sociability in comparison with the general Romanian population, although these differences must be interpreted with caution as the general Romanian population tend to be significantly younger. Conclusions: This study provides new insights into the role of personality traits as risk factors for burnout and work addiction, and as protective factors for stress-related growth in prehospital emergency personnel. It is also among the few studies in this field to employ the Alternative Five Factor Model of personality.

Background: This study presents a comprehensive analysis of cholesteatoma of the middle ear, focusing on its clinical presentation, diagnostic imaging, and treatment outcomes. Cholesteatomas are defined by the keratinized squamous epithelium within the middle ear, leading to significant bone erosion, often affecting the ossicular chain and surrounding structures. Methods: The study explores various mechanisms involved in cholesteatoma progression, including enzymatic lysis, inflammatory responses, and neurotrophic disturbances. The study conducted a retrospective clinical and statistical review of 580 patients over a 20-year period (2003–2023), highlighting the role of advanced imaging, including computed tomography (CT) and diffusion-weighted magnetic resonance imaging (DWI), in preoperative planning and postoperative follow-up. Results: Findings revealed that early detection and intervention are crucial in preventing severe complications such as intracranial infection and hearing loss. Surgical treatment primarily involved tympanoplasty and mastoidectomy, with a recurrence rate of 1.55% within two years. The study underscores the importance of integrating imaging advancements into clinical decision-making to enhance patient outcomes and suggests further investigation into molecular mechanisms underlying cholesteatoma progression and recurrence. Histopathological and microbiological analysis was performed to identify pathological patterns and microbial agents. Conclusions: The study highlights the importance of early diagnosis and intervention to prevent complications such as intracranial infections and permanent hearing loss, while also emphasizing the role of advanced imaging techniques in the management and long-term monitoring of cholesteatoma patients.

Point-of-care ultrasound (POCUS) is an essential component of emergency medicine, enabling rapid bedside assessment across a wide spectrum of acute conditions. Its effectiveness, however, remains constrained by operator dependency, variable image quality, and time-critical decision-making. Recent advances in artificial intelligence (AI) offer opportunities to augment POCUS by supporting image acquisition, interpretation, and quantitative analysis. This narrative review synthesizes current evidence on AI-enhanced POCUS applications in emergency care, encompassing trauma, non-traumatic emergencies, integrated workflows, resource-limited settings, and education and training. Across trauma settings, AI-assisted POCUS has demonstrated promising performance for automated detection of pneumothorax, hemothorax, and free intraperitoneal fluid, supporting standardized eFAST examinations and rapid triage. In non-traumatic emergencies, AI-enabled cardiovascular, pulmonary, and abdominal applications provide automated measurements and pattern recognition that can approach expert-level performance when image quality is adequate. Integrated AI–POCUS systems and educational tools further highlight the potential to expand ultrasound access, support non-expert users, and standardize training. Nevertheless, important limitations persist, including limited generalizability, dataset bias, device heterogeneity, and uncertain impact on clinical decision-making and patient outcomes. In conclusion, AI-enhanced POCUS is transitioning from proof-of-concept toward early clinical integration in emergency medicine. While current evidence supports its role as a decision-support tool that may enhance consistency and efficiency, widespread adoption will require prospective multicentre validation, development of representative POCUS-specific datasets, vendor-agnostic solutions, and alignment with clinical, ethical, and regulatory frameworks.