Recenti progressi in medicina最新文献

Hospital logistics automation applied to the dispensing of medicines to patients in care transition (hospital discharge or outpatient visit) offers significant opportunities to improve risk management and ensure the quality of healthcare. The adoption of technological innovation in hospital requires organizational changes, development of new workflows, collaboration between different professionals and acquisition of new skills. The logistics automation system was analyzed using NOISE analysis, as a strategic planning tool, in order to assess the impact of this innovation. The analysis highlighted the consistency of the innovation with local health policies, the assessment of feasibility in the hospital context and the reorganization focused on process optimization. As a result, operational steps were initiated leading to the acquisition of the new technology in February 2023. The application of strategic planning techniques to healthcare processes is crucial to ensure technological advancement in healthcare, the maximization of public investments and the development of a new professional culture capable of optimising innovations.

Triple-negative breast cancer (TNBC) poses a challenge due to high metastatic potential and few care options. The successful management of relapsed disease is an unmet clinical need, to date. The antibody drug conjugate sacituzumab govitecan (SG) has been an actual breakthrough in the metastatic TNBC (mTNBC) algorithm. Herein, we report the case of a 45-year-old patient, who was referred to our centre for a hard-to-treat locoregional relapse from TNBC, thus receiving SG in third-line setting for 15 months. We also discuss clinical presentation, treatment patterns and outcomes along with a brief literature review. Our case study outlines the long-term efficacy of third-line SG in a TNBC patient with a refractory disease. Thanks to SG use within a multimodal patient journey, a sustained disease control along with a preserved quality of life was gained. Further real-world data is awaited to confirm these findings.

Climate change has negative effects on mental health as shown by the World health organization (Who). Heatwaves can exacerbate some mental conditions such as schizophrenia and psychosis, both in the elderly and children as well as in young adults, and increase mortality for neurological and psychiatric diseases. Subjects facing climate events such as heavy rains and flooding may suffer from a psychological problem in the short, medium and long-term. Studies from the international and Italian context show that air pollution exposure may affect common mental problems such as depression and anxiety. Taking into account the growing trend in climate extremes, there is the need to deepen the knowledge on this topic to support the implementation of prevention and mitigation interventions.

The aim of this scoping review is to shed light on the current state of the art regarding ChatGPT's potential applications in clinical decision support, as well as its accuracy, sensitivity, speed, and reliability in different clinical contexts (diagnosis, differential diagnosis, treatment, triage, surgical support). Most of the articles found were original research articles, with a few reviews and commentaries. A total of 225 articles were found, of which 50 were included based on retrieval and eligibility. ChatGPT performs well in diagnosis with complete data but struggles with incomplete or ambiguous information. Its differential diagnosis is inconsistent, especially in complex cases. It shows good sensitivity in treatment recommendations but lacks personalization and requires human oversight. In triage, ChatGPT is accurate, with high sensitivity for hospitalization decisions but lower specificity for safe discharges. For surgical support, it aids in planning but cannot adapt to intraoperative changes without human input. The results indicate that ChatGPT has potential in supporting clinical decisions but also highlights significant current limitations; that include the need for medical-specific adaptation, the risk of generating false (artificial hallucinations), incomplete, or misleading information, and ethical and legal issues that need to be addressed.