A systematic review of air pollution and incidence of out-of-hospital cardiac arrest

Introduction: Studies have linked air pollution with the incidence of acute coronary artery events and cardiovascular mortality but the association with out-of-hospital cardiac arrest (OHCA) is less clear. Aim: To examine the association of air pollution with the occurrence of OHCA.Methods: Electronic bibliographic databases (until February 2013) were searched. Search terms included common air pollutants and OHCA. Studies of patients with implantable cardioverter defibrillators and OHCA not attended by paramedics were excluded. Two independent reviewers (THKT and TAW) identified potential studies. Methodological: quality was assessed by the Newcastle-Ottawa Scale.Results: Of 849 studies, 8 met the selection criteria. Significant associations between particulate matter (PM) exposure (especially PM2.5) and OHCA were found in 5 studies. An increase of OHCA risk ranged from 2.4% to 7% per interquartile increase in average PM exposure on the same day and up to 4 days prior to the event. A large study found ozone increased the risk of OHCA within 3 h prior to the event. The strongest risk OR of 3.8–4.6% per 20 parts per billion ozone increase of the average level was within 2 h prior to the event. Similarly, another study found an increased risk of 18% within 2 days prior to the event.Conclusions: Larger studies have suggested an increased risk of OHCA with air pollution exposure from PM 2.5 and ozone

A Unified Theoretical Description of the Thermodynamical Properties of Spin Crossover with Magnetic Interactions

After the discovery of the phenomena of light-induced excited spin state trapping (LIESST), the functional properties of metal complexes have been studied intensively. Among them, cooperative phenomena involving low spin-high spin (spin-crossover) transition and magnetic ordering have attracted interests, and it has become necessary to formulate a unified description of both phenomena. In this work, we propose a model in which they can be treated simultaneously by extending the Wajnflasz-Pick model including a magnetic interaction. We found that this new model is equivalent to Blume-Emery-Griffiths (BEG) Hamiltonian with degenerate levels. This model provides a unified description of the thermodynamic properties associated with various types of systems, such as spin-crossover (SC) solids and Prussian blue analogues (PBA). Here, the high spin fraction and the magnetization are the order parameters describing the cooperative phenomena of the model. We present several typical temperature dependences of the order parameters and we determine the phase diagram of the system using the mean-field theory and Monte Carlo simulations. We found that the magnetic interaction drives the SC transition leading to re-entrant magnetic and first-order SC transitions.Comment: 30pages, 11figure

Evidence-based paramedic models of care to reduce unnecessary emergency department attendance – feasibility and safety

Background: As demand for Emergency Department (ED) services continues to exceed increases explained by population growth, strategies to reduce ED presentations are being explored. The concept of ambulance paramedics providing an alternative model of care to the current default ‘see and transport to ED’ has intuitive appeal and has been implemented in several locations around the world. The premise is that for certain noncritical ill patients, the Extended Care Paramedic (ECP) can either ‘see and treat’ or ‘see and refer’ to another primary or community care practitioner, rather than transport to hospital. However, there has been little rigorous investigation of which types of patients can be safely identified and managed in the community, or the impact of ECPs on ED attendance.Methods/Design: St John Ambulance Western Australia paramedics will indicate on the electronic patient care record (e-PCR) of patients attended in the Perth metropolitan area if they consider them to be suitable to be managed in the community. ‘Follow-up’ will examine these patients using ED data to determine the patient’s disposition from the ED. A clinical panel will then develop a protocol to identify those patients who can be safely managed in the community. Paramedics will then assess patients against the derived ECP protocols and identify those deemed suitable to ‘see and treat’ or ‘see and refer’. The ED disposition (and other clinical outcomes) of these ‘ECP protocol identified’ patients will enable us to assess whether it would have been appropriate to manage these patients in the community. We will also ‘track’ re-presentations to EDs within seven days of the initial presentation. This is a ‘virtual experiment’ with no direct involvement of patients or changes in clinical practice. A systems modelling approach will be used to assess the likely impact on ED crowding.Discussion: To date the efficacy, cost-effectiveness and safety of alternative community-based models of emergency care have not been rigorously investigated. This study will inform the development of ECP protocols through the identification of types of patient presentation that can be considered both safe and appropriate for paramedics to manage in the community

Initial prehospital vital signs to predict subsequent adverse hospital outcomes

There is growing interest to improve identification of the critically ill patient in the prehospital setting.1–3 We aimed to assess whether initial vital physiological signs in the prehospital setting can predict subsequent adverse hospital outcomes, defined as intensive care (ICU) admission or death in the emergency department (ED). https://bmjopen.bmj.com/content/7/Suppl_3/A5.3 This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. http://creativecommons.org/licenses/by-nc/4.0/ DOI http://dx.doi.org/10.1136/bmjopen-2017-EMSabstracts.1

A qualitative study of systemic influences on paramedic decision making: care transitions and patient safety.

OBJECTIVES: Paramedics routinely make critical decisions about the most appropriate care to deliver in a complex system characterized by significant variation in patient case-mix, care pathways and linked service providers. There has been little research carried out in the ambulance service to identify areas of risk associated with decisions about patient care. The aim of this study was to explore systemic influences on decision making by paramedics relating to care transitions to identify potential risk factors. METHODS: An exploratory multi-method qualitative study was conducted in three English National Health Service (NHS) Ambulance Service Trusts, focusing on decision making by paramedic and specialist paramedic staff. Researchers observed 57 staff across 34 shifts. Ten staff completed digital diaries and three focus groups were conducted with 21 staff. RESULTS: Nine types of decision were identified, ranging from emergency department conveyance and specialist emergency pathways to non-conveyance. Seven overarching systemic influences and risk factors potentially influencing decision making were identified: demand; performance priorities; access to care options; risk tolerance; training and development; communication and feedback and resources. CONCLUSIONS: Use of multiple methods provided a consistent picture of key systemic influences and potential risk factors. The study highlighted the increased complexity of paramedic decisions and multi-level system influences that may exacerbate risk. The findings have implications at the level of individual NHS Ambulance Service Trusts (e.g. ensuring an appropriately skilled workforce to manage diverse patient needs and reduce emergency department conveyance) and at the wider prehospital emergency care system level (e.g. ensuring access to appropriate patient care options as alternatives to the emergency department)