Emergency Medicine Journal最新文献

Background: Out-of-hospital cardiac arrest (OHCA) shows marked geographic variability. Socio-economic deprivation may contribute to this variability, but evidence from mixed urban-rural regions remains limited. We aimed to identify spatial clusters of OHCA incidence in northern France and to assess whether these clusters were associated with deprivation, care processes and outcomes.

Methods: We conducted a retrospective, population-based cohort study using data from the French National Out-of-Hospital Cardiac Arrest Registry for all OHCAs managed by mobile intensive care units between 1 July 2015 and 30 June 2016 in Nord-Pas-de-Calais. Age-adjusted and sex-adjusted standardised incidence ratios were smoothed with a Besag-York-Mollié Bayesian model. Spatial scan statistics identified incidence clusters. Cluster-level socioeconomic indicators, care processes and outcomes were compared RESULTS: Incidence was mapped across 1541 municipalities. Among 2867 OHCAs, mean annual OHCA incidence was 68.8 per 100 000 inhabitants (range <0.5 to >1.5 across municipalities). Two high-incidence clusters (relative risk between 1.61 and 1.68) and three low-incidence clusters (relative risk between 0.48 and 0.66) were detected. High-incidence clusters displayed greater deprivation and lower median income. Bystander basic life support was less frequent (26.7%) and 12-month survival lowest (1.4%) in the most deprived cluster.

Conclusions: Pronounced spatial inequality in OHCA burden exists within northern France. Municipalities with higher deprivation experience disproportionately higher incidence and poorer long-term survival. Targeted cardiopulmonary resuscitation training and strategic automated external defibrillator deployment should prioritise these vulnerable communities.

The Urgent and Emergency Care system generates a wealth of clinical information, but our ability to harness this for public health planning and to address health inequalities is constrained by systemic data quality issues. Modern natural language processing (NLP), driven by the context-aware capabilities of transformer-based architectures and large language models, offers a transformative opportunity to bridge this gap. By training machines to interpret and structure context-rich clinical notes at scale, we can translate complex patient stories into data ready for research and systems intelligence that reflects the realities of real-world care.This technology offers a potential route to addressing health inequities in vulnerable populations, such as those presenting with crises related to mental ill-health, alcohol and drug use. Current reliance on structured but oversimplistic data often fails to capture the complex intersectionalities of clinical and social contexts. This is due to factors like diagnostic overshadowing and unrecorded multimorbidity, leaving these patients statistically obscured within routine datasets, which fail to accurately represent volume or complexity. This data invisibility perpetuates a cycle of inaccurate disease burden estimates, under-resourced services and flawed policy. By unlocking the detailed narrative data within unstructured notes, NLP could allow us to identify the acute social stressors and psychiatric contexts that are currently invisible, making these inequities visible and actionable.

Background: Female patients who experience out-of-hospital cardiac arrest (OHCA) are less likely to receive bystander cardiopulmonary resuscitation (CPR) than male patients. However, the interaction between the patient and the sex of the bystander in CPR provision remains underexplored. Therefore, this study aimed to investigate the interaction between patient and sex of bystander in CPR provision during OHCA and to assess CPR rates based on dispatcher-assisted CPR (DA-CPR) administration status.

Methods: This cohort study used prospectively collected nationwide registry data between January 2019 and June 2023. Adult patients with medical aetiology of OHCA who were transported by emergency medical services were included. The primary outcome was bystander CPR provision according to sex. The secondary outcome was the provision of bystander CPR based on DA-CPR administration status.

Results: A total of 6487 patients with OHCA were included (median (IQR) age: 55 (52-64) years; male bystanders treated 3977 patients (61.3%)). The bystander CPR rate was lower when the patient and sex of bystander differed (male patient-male bystander, 85.0% vs male patient-female bystander, 79.2%; female patient-male bystander, 79.5% vs female patient-female bystander, 82.1%). Female bystanders were less likely to provide bystander CPR than male bystanders (adjusted OR (aOR): 0.83, 95% CI 0.73 to 0.95). The odds of a female bystander providing CPR to a male patient were significantly lower than those of a male bystander (aOR: 0.684, 95% CI 0.578 to 0.810). This difference was reduced when DA-CPR was administered (without DA-CPR, aOR: 0.673, 95% CI 0.475 to 0.952 vs with DA-CPR, aOR: 0.822, 95% CI 0.706 to 0.957).

Conclusion: An interaction between the patient and the sex of bystander was observed, particularly when the patient was a male and the bystander was a female. DA-CPR may serve as a potential intervention to help mitigate this disparity.

Background: A significant challenge to achieving global 2030 elimination goals for blood-borne viruses (BBVs) is identifying undiagnosed individuals and relinking those who are no longer in care. To address this, the UK government has implemented opt-out BBV testing in emergency departments (EDs) to increase access to BBV testing in high prevalence areas. All adult ED patients having a routine blood test are automatically tested for HIV, hepatitis B and C, unless they opt out. This study aimed to identify barriers and facilitators to the implementation of ED opt-out BBV testing and provide recommendations for future rollouts.

Method: Semi-structured interviews with 23 staff members across five ED sites in very high HIV prevalence areas were analysed thematically, informed by Normalisation Process Theory.

Results: While there was some variation in staff knowledge and understanding of the programme, overall acceptance of the opt-out testing approach was found to be high. Training had a positive impact on staff understanding of the purpose of the intervention and the correct process, including the opt-out model. High workloads and competing priorities in EDs were significant barriers to testing. However, some specific systems and processes that facilitated the uptake of testing included automation and BBV champions. Giving the programme time to embed into practice and ensuring feedback loops and flexibility to 'tweak' the process was also essential to sustaining the programme.

Conclusion: To embed opt-out testing into emergency care, sites should implement automated test ordering, staff training, clear communication and dedicated champions, which can help to support earlier diagnosis, reduce inequalities and improve patient outcomes.