BMC Emergency Medicine最新文献

{"title":"Psychosocial working conditions and violence prevention climate in German emergency departments - a cross-sectional study.","authors":"Sonja Reißmann, Mannat Guliani, Tanja Wirth, David A Groneberg, Volker Harth, Stefanie Mache","doi":"10.1186/s12873-024-01155-y","DOIUrl":"10.1186/s12873-024-01155-y","url":null,"abstract":"<p><strong>Background: </strong>Emergency departments (EDs) are high pressure work environments with several psychosocial job demands, e.g., violence, and job resources, e.g., colleague support. So far, the perceptions of working conditions have been compared between doctors and nurses, but there is limited knowledge regarding their respective supervisors. In addition, the violence prevention climate has not been assessed in German EDs before. Thus, the current study focuses on differences in the perceptions of working conditions and the violence prevention climate between the groups of doctor-supervisors, doctor-employees, nurse-supervisors, and nurse-employees within the ED. Further analyses regarding the association between social relations and pressure for unsafe practices are performed, including the moderating role of belonging to one of the aforementioned groups.</p><p><strong>Methods: </strong>A cross-sectional online survey was carried out among N = 370 participants, who were doctors or nurses from German EDs. The Questionnaire for Psychosocial Risk Assessment (QPRA) and the Violence Prevention Climate Scale (VPCS) were applied. Kruskal-Wallis tests were performed for group comparisons, followed by a hierarchical multiple linear regression model and moderation analyses.</p><p><strong>Results: </strong>Statistically significant differences between the groups were found for eight out of 13 variables. The highest number of significant pairwise comparisons was found between the groups of doctor-supervisors and nurse-employees. High job demands regarding work intensity and work interruptions became apparent across all groups. Nurse-employees reported the highest social and emotional demands as well as the highest pressure for unsafe practices regarding violence prevention, significantly differing from the other groups on these variables. The variables of supervisor support and social stressors were found to be significantly predictive of pressure for unsafe practices. Furthermore, there was no moderating effect of belonging to one of the above-mentioned groups in the relationships between variables of social relations and pressure for unsafe practices.</p><p><strong>Conclusions: </strong>Differences found in the current study can help tailor preventive measures according to the needs of distinct professions and positions in order to improve working conditions and the violence prevention climate in EDs. Furthermore, supervisor support should be strengthened while social stressors should be resolved in order to decrease pressure for unsafe practices regarding violence prevention.</p>","PeriodicalId":9002,"journal":{"name":"BMC Emergency Medicine","volume":"25 1","pages":"17"},"PeriodicalIF":2.3,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11759433/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143027884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparison of search and rescue operations involving emergency physicians in devastating earthquakes in Turkey: a 24-year experience study.","authors":"Mustafa Ferudun Celikmen, Gülbin Aydoğdu Umaç, Melih Imamoglu, Mümin Murat Yazici, Elif Çiğdem Keleş, Sarper Yilmaz","doi":"10.1186/s12873-025-01174-3","DOIUrl":"10.1186/s12873-025-01174-3","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;In the 21st century, disasters (particularly earthquakes, which remain the leading cause of death) continue to be among the foremost issues requiring global emergency response. While the impact of advancing technologies on the environmental and human damage caused by earthquakes is still a subject of debate, search and rescue (SAR) teams and emergency departments (ED), specifically emergency physicians (EPs), play a crucial role in the most acute management of the effects of these earthquakes on human life. This study aims to examine the injury dynamics of two catastrophic earthquakes that occurred in Turkey 24 years apart from the perspective of EPs, utilizing archival records from the SAR teams in which EPs served.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Method: &lt;/strong&gt;This study is a cross-sectional investigation analyzing the injury and SAR dynamics of casualties, based on the archives of SAR teams that included 12 EPs, during the 1999 Marmara and 2023 Kahramanmaraş (Maraş) earthquakes (groups).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;In this study, a total of 160 injured individuals who were rescued alive from the rubble were included, with 26.3% (n = 42) from the Maraş group and 73.8% (n = 118) from the Marmara group. Identification of the injured was achieved in 54.8% (n = 23) of the Maraş group and 88.1% (n = 104) of the Marmara group, with an overall identification rate of 79.4% (n = 127) (p &lt; 0.001). The most common injuries among the injured were lower extremity injuries (53.1%, n = 85) and upper extremity injuries (49.4%, n = 79), with the most frequent scenario being the extraction of two individuals from the same location (33.8%, n=54). The most common interventions provided to the injured were intravenous fluid therapy (63.8%, n =102) and oxygen support (57.5%, n =92). The rate of intubation at the scene was 16.1% (n = 19) in the Marmara group and 4.8% (n = 2) in the Maraş group (p &lt; 0.05). Additionally, cardiopulmonary resuscitation (CPR) was administered at the scene in 13.6% (n = 16) of the Marmara group, compared to 2.4% (n = 1) in the Maraş group (p &lt; 0.05). When examining the challenges encountered during SAR operations, the most frequent issue in the Maraş group was identification, affecting 57.1% of the cases (p &lt; 0.001), whereas the most common issue in the Marmara group was entrapment, occurring in 50.0% of cases (p &lt; 0.001). Lighting difficulties were observed at similar rates in both earthquakes (19.0% in Maraş, 19.5% in Marmara; p = 1.000). Additionally, weather conditions posed a challenge in 11.9% of cases in the Maraş group, whereas this issue was not encountered in the Marmara group (p &lt; 0.001).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusion: &lt;/strong&gt;The 24 years of experience and expertise gained by EPs who served in Türkiye in these operations constitute a valuable global resource. Disseminating this knowledge is crucial not only for managing earthquakes but also for preparing for other catastrophic events that could cause widespread","PeriodicalId":9002,"journal":{"name":"BMC Emergency Medicine","volume":"25 1","pages":"10"},"PeriodicalIF":2.3,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11737226/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142999596","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Understanding and measuring workplace violence in healthcare: a Canadian systematic framework to address a global healthcare phenomenon.","authors":"Christian Schulz-Quach, Brendan Lyver, Charlene Reynolds, Trevor Hanagan, Jennifer Haines, John Shannon, Laura Danielle Pozzobon, Yasemin Sarraf, Sam Sabbah, Sahand Ensafi, Natasha Bloomberg, Jaswanth Gorla, Brendan Singh, Lucas B Chartier, Marnie Escaf, Diana Elder, Marc Toppings, Brian Hodges, Rickinder Sethi","doi":"10.1186/s12873-024-01144-1","DOIUrl":"10.1186/s12873-024-01144-1","url":null,"abstract":"<p><strong>Background: </strong>Globally, healthcare institutions have seen a marked rise in workplace violence (WPV), especially since the Covid-19 pandemic began, affecting primarily acute care and emergency departments (EDs). At the University Health Network (UHN) in Toronto, Canada, WPV incidents in EDs jumped 169% from 0.43 to 1.15 events per 1000 visits (p < 0.0001). In response, UHN launched a comprehensive, systems-based quality improvement (QI) project to ameliorate WPV. This study details the development of the project's design and key takeaways, with a focus on presenting trauma-informed strategies for addressing WPV in healthcare through the lens of health systems innovation.</p><p><strong>Methods: </strong>Our multi-intervention QI initiative was guided by the Systems Engineering Initiative for Patient Safety (SEIPS) 3.0 framework. We utilized the SEIPS 101 tools to aid in crafting each QI intervention.</p><p><strong>Results: </strong>Using the SEIPS 3.0 framework and SEIPS 101 tools, we gained a comprehensive understanding of organizational processes, patient experiences, and the needs of HCPs and patient-facing staff at UHN. This information allowed us to identify areas for improvement and develop a large-scale QI initiative comprising 12 distinct subprojects to address WPV at UHN.</p><p><strong>Conclusions: </strong>Our QI team successfully developed a comprehensive QI project tailored to our organization's needs. To support healthcare institutions in addressing WPV, we created a 12-step framework designed to assist in developing a systemic QI approach tailored to their unique requirements. This framework offers actionable strategies for addressing WPV in healthcare settings, derived from the successes and challenges encountered during our QI project. By applying a systems-based approach that incorporates trauma-informed strategies and fosters a culture of mutual respect, institutions can develop strategies to minimize WPV and promote a safer work environment for patients, families, staff, and HCPs.</p>","PeriodicalId":9002,"journal":{"name":"BMC Emergency Medicine","volume":"25 1","pages":"9"},"PeriodicalIF":2.3,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11727261/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142969586","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modelling emergency response times for Out-of-Hospital Cardiac Arrest (OHCA) patients in rural areas of the North of England using routinely collected data.","authors":"Megan Harries, Anastasia Ushakova","doi":"10.1186/s12873-025-01170-7","DOIUrl":"10.1186/s12873-025-01170-7","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;National response time targets for ambulance services are known to be more strongly maintained in urban areas compared to rural. That may mean that responses in rural areas could be less immediate which can in turn affect survival of those experiencing cardiac arrest. Thus, analysis of variation in response times using routinely collected data can be used to understand which rural areas have the highest need for emergency intervention. In this study we have focused, given the heterogeneity of demographic make up, on a specific area of the North of England. Some areas in North England have shown to have a large proportion of cardiac arrests occurring in a rural setting, specifically, in the anonymised study region this was almost half of the cases at 46.3%. Response times to these areas were found to be over 3.5 minutes slower than for urban areas making it worthy of further exploration.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;A retrospective observation analysis was conducted on routinely collected data from regional ambulance services for areas within the North of England from April 2016 to March 2021. Information was collected on service and geographic characteristics for 1915 incidents. A multivariable linear mixed effect regression model was used to understand the association between geographical, service factors and response times to cardiac arrest patients. To advance previous research which up to now only used visualisations to analyse ambulance response times, the study used a mixed effects model with a variety of predictors, capturing geographical variation alongside service characteristics.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;From the cases analysed it was found that the mean response time to scene was 9.1 minutes, with a standard deviation of 6.4 minutes. After adjustment for geographic variation and incorporating robust standard errors into the model: distance to the nearest ambulance station (coefficient = 0.61, 95% confidence interval [CI]: 0.56-0.66), urgency of the call (Category 2, second most urgent, compared to the most urgent coefficient = 1.66, 95% CI: 1.13 - 2.18), location of the nearest ambulance station to the incident and the type of crew who attended the incident (Advanced Paramedic when compared to just Paramedic, coefficient = -0.70, 95% CI: -1.24 - -0.16) were all factors which affected response times to scene.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusion: &lt;/strong&gt;For each extra km the incident was away from an ambulance station, the response time to scene increased by 37 seconds. The ambulance station which displayed the largest increase in response time, Station L was 170 seconds (95% CI: 79, 261) longer than Station N, which had a median performance across all stations, as measured by median survival rate to return of spontaneous circulation (ROSC). The rural geography of the North of England means that lots of cardiac arrest incidents occur a considerable distance away from the stations, emphasising the need to ","PeriodicalId":9002,"journal":{"name":"BMC Emergency Medicine","volume":"25 1","pages":"8"},"PeriodicalIF":2.3,"publicationDate":"2025-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11724540/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142963731","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Paramedics and emergency medical technicians' perceptions of geriatric trauma care in Saudi Arabia.","authors":"Naif Harthi, Steve Goodacre, Fiona C Sampson, Meshary Binhotan, Abdullah Suhail Alotaibi","doi":"10.1186/s12873-024-01167-8","DOIUrl":"10.1186/s12873-024-01167-8","url":null,"abstract":"<p><strong>Background: </strong>Saudi ambulance clinicians face unique challenges in providing prehospital care to older trauma patients. Limited geriatric-specific training and complex needs of this population hinder effective management, leading to adverse outcomes. This study explores the perceptions of Saudi ambulance clinicians regarding geriatric trauma care and identify facilitators and barriers to improved care.</p><p><strong>Methods: </strong>A qualitative study was conducted using a purposive sample of Saudi paramedics and ambulance technicians from Riyadh and Makkah using online semi-structured interviews and analysed using the framework method.</p><p><strong>Results: </strong>The qualitative study recruited twenty participants and identified that they reported age-related challenges including physiological changes, polypharmacy, and communication difficulties. They all wanted training and guidelines to improve their knowledge. They reported struggling with communication difficulties, inaccurate adverse outcomes predictions, difficult intravenous cannulations, and cultural restrictions affecting care provision for female patients. We identified organisational barriers (e.g. lack of shared patient records and lack of guidelines) and cultural barriers (e.g. barriers to assessing women, attitudes towards older people, and attitudes towards paramedics) that influenced implementation of knowledge.</p><p><strong>Conclusion: </strong>Ambulance clinicians in Saudi Arabia want guidelines and training in managing older trauma patients but these need to take into account the organisational and cultural barriers that we identified to facilitate implementing knowledge and changing practice to providing improved care.</p>","PeriodicalId":9002,"journal":{"name":"BMC Emergency Medicine","volume":"25 1","pages":"6"},"PeriodicalIF":2.3,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11715434/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142944143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction of post-contrast acute kidney injury by bedside ultrasonography.","authors":"Mümin Murat Yazici, Enes Hamdioğlu, Nurullah Parça, Gürkan Altuntaş, Özcan Yavaşi, Özlem Bilir","doi":"10.1186/s12873-025-01172-5","DOIUrl":"10.1186/s12873-025-01172-5","url":null,"abstract":"<p><strong>Background: </strong>The incidence of contrast-induced acute kidney injury (CI-AKI) in the general population ranges from 0.6 to 2.3%, whereas for specific high-risk patients, the incidence can reach more than 30-40%. Ultrasound measurements of the development of CI-AKI after contrast-enhanced imaging for diagnosis in the emergency department (ED) have yet to be adequately studied. Accordingly, we aimed to evaluate the usefulness of Doppler ultrasound measurements for predicting CI-AKI in patients with normal renal function.</p><p><strong>Methods: </strong>This prospective, observational, single-center study was conducted in the ED of a tertiary teaching and research hospital between 1 January and 1 July 2024. All patients who presented to the tertiary training and research hospital ED, who were admitted to the hospital with a decision to undergo contrast-enhanced tomography for diagnosis, and who did not meet any exclusion criteria were included in the study. Patients included in the study were evaluated by ultrasonographic measurements (interlobar renal artery peak systolic velocity (PSV), interlobar renal artery end-diastolic velocity (EDV), inferior vena cava (IVC) collapsibility index, and renal resistive index (RRI)).</p><p><strong>Results: </strong>The postcontrast RRI cutoff values were calculated to predict CI-AKI. The area under the curve (AUC) for the postcontrast RRI was 0.914, and the cutoff value for the postcontrast RRI was 0.70 (≥), exhibiting 72.7% sensitivity and 95.6% specificity.</p><p><strong>Conclusion: </strong>Postcontrast RRI ultrasound measurements performed after diagnostic contrast imaging in the ED show high specificity in predicting CI-AKI development. Postcontrast ultrasound measurements may predict CI-AKI development, allowing further measures to be taken. Further studies are needed to confirm these findings.</p><p><strong>Trial registration: </strong>Clinical trial number: not applicable.</p>","PeriodicalId":9002,"journal":{"name":"BMC Emergency Medicine","volume":"25 1","pages":"7"},"PeriodicalIF":2.3,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11715197/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142944149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Outcomes of an Emergency Department opioid alternatives Program implemented within a safety-net hospital system.","authors":"Magda Montague, Charlotte Hopson, Claire Layton, Jennifer Fishe, Ashley Norse, L Kendall Webb, Petra Duran-Gehring, Andrew Bertrand, Jennifer Brailsford, Taylor Munson, Rui Wang, Nolan Menze, Katelyn Perl, Phyllis Hendry, Sophia Sheikh","doi":"10.1186/s12873-024-01168-7","DOIUrl":"https://doi.org/10.1186/s12873-024-01168-7","url":null,"abstract":"<p><strong>Background: </strong>The ongoing opioid epidemic in the United States has reinforced the need to provide multimodal and non-opioid pain management interventions. The PAMI-ED ALT program employed a multifaceted approach in the Emergency Department (ED) developing electronic health record (EHR) pain management order panels and discharge panels, as well as educating patients, clinicians, and ED staff on opioid alternatives, including non-pharmacologic interventions. The primary objective of this analysis was to compare changes in opioid and non-opioid analgesic administrations and prescribing in ED patients with select pain conditions (renal colic, headache, low back, and non-low back musculoskeletal pain) before and after implementation of PAMI ED-ALT. Secondary outcomes included characterizing changes in 30-day ED all-cause recidivism and hospital all-cause admissions within these pain populations.</p><p><strong>Methods: </strong>Demographics, opioid and opioid alternative utilization, hospital admission, 30-day ED returns and change in pain intensity score were collected from January 2019-March 2020 (pre-program implementation) and January 2021-March 2023 (post-program implementation) for both the ED aggregate and program target pain populations.</p><p><strong>Results: </strong>Pain management order panel utilization increased throughout the post-implementation period. When comparing pre to post program data, there was a reduction in opioid administrations and prescriptions for most of the target pain conditions, as well as within the ED aggregate population. Opioid alternative administrations and prescriptions increased for all pain conditions except renal colic. Hospital admissions decreased significantly amongst those with low back pain and headache/migraine and 30-day ED returns significantly declined in those with musculoskeletal pain.</p><p><strong>Conclusion: </strong>Our findings demonstrate an opioid-alternatives program implemented within a safety-net hospital system serving a predominantly socially disadvantaged patient population can lead to changes in ED pain management and potentially reduce 30-day ED recidivism and hospitalizations.</p>","PeriodicalId":9002,"journal":{"name":"BMC Emergency Medicine","volume":"25 1","pages":"5"},"PeriodicalIF":2.3,"publicationDate":"2025-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11707854/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142944139","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"TiMON: a real-time integrated monitor for improving the placement and wear of emergency tourniquets.","authors":"John Quan Nguyen, Avery Goss, Helen Keshishian, Francis Berchard, Jonathan Parks, Conor Evans","doi":"10.1186/s12873-024-01169-6","DOIUrl":"https://doi.org/10.1186/s12873-024-01169-6","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;The use of emergency tourniquets among military personnel has helped to dramatically reduce battlefield deaths and has recently gained popularity in the civilian sector. Yet, even well-trained individuals can find it difficult to assess proper tourniquet application. Emergency tourniquets are typically deemed sufficiently tightened through cursory visual confirmation or pulse assessment. These indicators are not always accurate and are difficult to assess during chaotic events where fast and effective tourniquet application by both trained and untrained personnel can contribute significantly to saving lives. Towards addressing these issues, we have developed the Tourniquet Integrated Monitor (TiMON) as an easy-to-use real-time pressure sensing device designed to seamlessly integrate with pre-existing emergency tourniquets. Here, we present the results of two studies in which the TiMON was tested among a group of soldiers participating in the Army Expeditionary Warrior Experiments (AEWE) as well as in a group of untrained civilians from Massachusetts General Hospital.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;In the first study, 30 soldiers with prior tourniqueting experience were asked to apply a TiMON equipped CAT tourniquet onto a leg mannequin with (unblinded) and without (blinded) assistance from the TiMON's output. In the second study, 30 lay volunteers from Massachusetts General Hospital with no prior tourniquet training were recruited and taught how to apply a tourniquet under normal conditions prior to being asked to perform the same exercises as the soldiers. In both studies, data collected for statistical analysis consisted of the real-time applied pressure along with the elapsed time for each subject to finish applying the emergency tourniquet.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Subjects in both groups utilizing the TiMON had greater success in applying emergency tourniquets at the civilian clinically recommended occlusion range of 180 to 300 mmHg (soldiers: 86.67% assisted vs 33.33% unassisted; untrained volunteers: 93.33% assisted vs 40.00% unassisted). In terms of applied pressure, no significant mean differences were observed in either group (soldiers p-value = 0.13; untrained volunteers p-value = 0.26), however the unblinded subjects were found to exhibit significantly lower variances in applied pressure compared to those who were blinded (soldiers p-value &lt; 0.0001; untrained volunteers p-value &lt; 0.0001). In terms of application speeds, no significant differences in means and variances were observed in the soldiers (p-values = 0.85 and 0.61, respectively), while mildly significant increases in application times were observed in the untrained volunteers (p-value = 0.036).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusion: &lt;/strong&gt;Trained soldiers and lay volunteers using the TiMON were able to consistently apply tourniquets at clinically recommended occlusion pressures between 180 and 300 mmHg with significantly less under and over tigh","PeriodicalId":9002,"journal":{"name":"BMC Emergency Medicine","volume":"25 1","pages":"4"},"PeriodicalIF":2.3,"publicationDate":"2025-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11705624/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142944151","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting emergency department admissions using a machine-learning algorithm: a proof of concept with retrospective study.","authors":"Cyrielle Brossard, Christophe Goetz, Pierre Catoire, Lauriane Cipolat, Christophe Guyeux, Cédric Gil Jardine, Mahuna Akplogan, Laure Abensur Vuillaume","doi":"10.1186/s12873-024-01141-4","DOIUrl":"https://doi.org/10.1186/s12873-024-01141-4","url":null,"abstract":"<p><strong>Introduction: </strong>Overcrowding in emergency departments (ED) is a major public health issue, leading to increased workload and exhaustion for the teams, resulting poor outcomes. It seems interesting to be able to predict the admissions of patients in the ED.</p><p><strong>Aim: </strong>The main objective of this study was to build and test a prediction tool for ED admissions using artificial intelligence.</p><p><strong>Methods: </strong>We performed a retrospective multicenter study in two French ED from January 1st, 2010 to December 31st, 2019.We tested several machine learning algorithms and compared the results.</p><p><strong>Results: </strong>The arrival and departure times from the ED of 2 hospitals were collected from all consultations during the study period, then grouped into 87 600 one-hour slots. Through the development of two models (one for each location), we found that the XGBoost method with hyperparameter adaptations was the best, suggesting that the studied data could be predicted (mean absolute error) at 2.63 for Hospital 1 and 2.64 for Hospital 2).</p><p><strong>Conclusions: </strong>This study ran the construction and validation of a powerful tool for predicting ED admissions in 2 French ED. This type of tool should be integrated into the overall organization of an ED, to optimize the resources of healthcare professionals.</p>","PeriodicalId":9002,"journal":{"name":"BMC Emergency Medicine","volume":"25 1","pages":"3"},"PeriodicalIF":2.3,"publicationDate":"2025-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11706136/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142944146","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advancing a machine learning-based decision support tool for pre-hospital assessment of dyspnoea by emergency medical service clinicians: a retrospective observational study.","authors":"Wivica Kauppi, Henrik Imberg, Johan Herlitz, Oskar Molin, Christer Axelsson, Carl Magnusson","doi":"10.1186/s12873-024-01166-9","DOIUrl":"10.1186/s12873-024-01166-9","url":null,"abstract":"<p><strong>Background: </strong>In Sweden with about 10 million inhabitants, there are about one million primary ambulance missions every year. Among them, around 10% are assessed by Emergency Medical Service (EMS) clinicians with the primary symptom of dyspnoea. The risk of death among these patients has been reported to be remarkably high, at 11,1% and 13,2%. The aim was to develop a Machine Learning (ML) model to provide support in assessing patients in pre-hospital settings and to compare them with established triage tools.</p><p><strong>Methods: </strong>This was a retrospective observational study including 6,354 patients who called the Swedish emergency telephone number (112) between January and December 2017. Patients presenting with the main symptom of dyspnoea were included which were recruited from two EMS organisations in Göteborg and Södra Älvsborg. Serious Adverse Event (SAE) was used as outcome, defined as any of the following:1) death within 30 days after call for an ambulance, 2) a final diagnosis defined as time-sensitive, 3) admitted to intensive care unit, or 4) readmission within 72 h and admitted to hospital receiving a final time-sensitive diagnosis. Logistic regression, LASSO logistic regression and gradient boosting were compared to the Rapid Emergency Triage and Treatment System for Adults (RETTS-A) and National Early Warning Score2 (NEWS2) with respect to discrimination and calibration of predictions. Eighty percent (80%) of the data was used for model development and 20% for model validation.</p><p><strong>Results: </strong>All ML models showed better performance than RETTS-A and NEWS2 with respect to all evaluated performance metrics. The gradient boosting algorithm had the overall best performance, with excellent calibration of the predictions, and consistently showed higher sensitivity to detect SAE than the other methods. The ROC AUC on test data increased from 0.73 (95% CI 0.70-0.76) with RETTS-A to 0.81 (95% CI 0.78-0.84) using gradient boosting.</p><p><strong>Conclusions: </strong>Among 6,354 ambulance missions caused by patients suffering from dyspnoea, an ML method using gradient boosting demonstrated excellent performance for predicting SAE, with substantial improvement over the more established methods RETTS-A and NEWS2.</p>","PeriodicalId":9002,"journal":{"name":"BMC Emergency Medicine","volume":"25 1","pages":"2"},"PeriodicalIF":2.3,"publicationDate":"2025-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11702062/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142930667","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}