Acute Medicine最新文献

The Society for Acute Medicine (SAM) and Intensive Care Society (ICS) have produced joint guidance on the standards of care and infrastructure required to deliver enhanced care within Acute Medicine. The cohort of patients this relates to are in the most part already being looked after on the AMU, but co-location and providing enhanced monitoring and nursing input will ensure safe, high-quality care can be delivered to them. We strongly support the development of enhanced care units, whilst clearly acknowledging that they are not a replacement for critical care where that is indicated. Enhanced care and critical care complement each other and will help foster the close working between the two specialties that modern acute care requires. This guidance draws on expertise and existing relevant guidance from the two societies, alongside that from the Faculty of Intensive Care Medicine (FICM), British Thoracic Society (BTS), National Institute for Health and Care Excellence (NICE) and NHS England / Improvement (NHSE/I). We recognise this is an area with limited evidence and so will aim to review it regularly as the knowledge and experience in this area increases.

Listeria Monocytogenes is transmitted via ingestion of contaminated food products and can cause invasive disease in susceptible hosts. Risk factors include immunocompromise; pregnancy; being elderly; and new-born. Listeriosis is uncommon but can occur in immunocompetent individuals and has a high mortality rate. We report a case of a 62-year-old female with no obvious risk factors who presented with atypical meningism. The patient was subsequently diagnosed with listeria meningitis and made a good recovery. The patient was a gardener regularly handling soil and ingested vegetables from her allotment patch; this case is reported to highlight less common risk factors and atypical ways in which listeria may present to the acute medical take.

This commentary explores the potential impact of artificial intelligence (AI) in acute medicine, considering its possibilities and challenges. With its ability to simulate human intelligence, AI holds the promise for supporting timely decision-making and interventions in acute care. While AI has significantly contributed to improvements in various sectors, its implementation in healthcare remains limited. The development of AI tools tailored to acute medicine can improve clinical decision-making, and AI's role in streamlining administrative tasks, exemplified by ChatGPT, may offer immediate benefits. However, challenges include uniform data collection, privacy, bias, and preserving the doctor-patient relationship. Collaboration among AI researchers, healthcare professionals, and policymakers is crucial to harness the potential of AI in acute medicine and create a future where advanced technologies synergistically enhance human expertise.

Objective: To compare the SUHB mobility scale (i.e., stable(S), unstable gait(U), needing help to walk(H), or bedridden(B)) and the Emergency Severity Index (ESI) associations with admission and mortality outcomes.

Design: Post-hoc analysis of a prospective observational study including all consenting presenting to the ED over a period of 3 weeks. Odd ratios and AUCs were calculated to assess predictive performance of SUHB and compared with ESI.

Results: Out of 2422 patients, 65% presented with a stable gait, 45% with an ESI level 3. With increasing mobility impairment on the SUHB scale, the probability for admission and mortality increased. SUHB had a higher AUC than ESI for 1-year mortality.

Conclusion: SUHB was a better predictor than ESI of long-term mortality. The scale, which is rapid, requires little additional training, and no extra costs, could be used as a useful supplement to the triage process.