Trauma severity scores such as the Injury Severity Score (ISS) and New Injury Severity Score (NISS) are widely used for trauma benchmarking, risk stratification and outcome prediction, but rely on diagnostic imaging unavailable in the prehospital setting. We developed and externally validated the Prehospital Injury Severity Estimate (PHISE), a simple, scene-based score designed to be applied using clinical examination and knowledge of the injury mechanism. PHISE was retrospectively derived from the National Trauma Data Bank® (NTDB®) by mapping AIS-coded injury descriptions to eight PHISE body regions and four severity levels, using Large Language Model-assisted inference to identify imaging requirements and distinguish clinically assessable injuries. In the NTDB® cohort, PHISE score demonstrated strong correlation and calibration with ISS and NISS but lower predictive performance for outcomes including in-hospital mortality and blood transfusion need. External validation used the multinational TraumaRegister DGU®, which reports real-world data of a simplified prehospital injury score compatible to PHISE. Here, PHISE underperformed ISS/NISS in predicting mortality but achieved comparable performance for transfusion prediction. When embedded into machine learning models alongside prehospitally available patient variables, the performance gap to ISS/NISS narrowed further. PHISE provides a pragmatic, imaging-independent anatomical component for earlier AI-assisted trauma stratification in prehospital emergency care.

BACKGROUND:Trauma is a major global cause of morbidity and mortality, with haemorrhage representing a leading preventable cause of early death. Timely blood transfusion is a crucial intervention, but current prehospital decision-making tools are scarce. Conventional triggers, such as haemoglobin concentrations, are often unreliable in the acute setting. There is a clear need for more robust, data-driven methods to guide transfusion decisions before hospital arrival. METHODS:We conducted a retrospective, machine learning development and validation study to predict the need for prehospital transfusion in patients with trauma using readily available prehospital data, including vital signs, injury patterns, and anticoagulant medication taken before hospitalisation occurred. The models were trained on data obtained from 364 350 patients in the American National Trauma Data Bank from Jan 1 to Dec 31, 2020, and externally validated on data from 54 210 patients from three additional trauma registries (TraumaRegister DGU, National Office of Clinical Audit-Major Trauma Audit, and Alberta Trauma Registry of Alberta Health Services), covering cases from Germany, Austria, Switzerland, Ireland, and Canada between Jan 1, 2007, and Sept 30, 2024. Binary classifiers were trained for individual blood products, while a multiclass model predicted optimal transfusion combinations, and a regressor for the optimal amount of packed red blood cells (PRBCs). FINDINGS:The machine learning models demonstrated high predictive accuracy in identifying patients requiring transfusion. In the external validation cohort, the area under the receiver operating characteristic curve for predicting any transfusion need was 0·87 (95% CI 0·86-0·87), and was 0·88 (0·87-0·89) for PRBCs. The machine learning-based predictions outperformed laboratory-based risk stratification upon emergency department arrival. Stratification into transfusion probability groups showed that patients in the high transfusion probability group (predicted transfusion probability >0·5) had the highest incidence of overall mortality (padjusted=3·16 × 10-136), haemorrhagic death (padjusted=2·31 × 10-08), need for early operative bleeding control (padjusted=3·58 × 10-83), or timely transfusion (padjusted<2·2 × 10-308) compared with the low transfusion probability group (predicted probability <0·1), supporting the prognostic value of the approach. INTERPRETATION:Machine learning-based prediction of transfusion needs enables prehospital identification of patients at high risk for haemorrhagic shock, supporting early intervention and resource mobilisation. This strategy might improve outcomes by facilitating timely availability of blood products. Our findings support the potential use of artificial intelligence-driven decision support tools into emergency trauma care workflows, but further confirmation is needed with prospective usability and effectiveness studies before clinical implementation. FUNDING:None.

BackgroundPrompt identification of critically ill or injured patients is crucial for the quality of care in the event of a mass casualty incident. Rapid triage systems should be used to achieve this goal. To date, no information is available about the regional distribution of and familiarity with these instruments in Germany. ObjectiveThis study aims to provide an initial assessment of the triage systems established in Germany and their regional distribution based on information from paramedics and emergency physicians. Materials and methodsAn online survey of sociodemographic data as well as knowledge of various algorithms and their practical use was conducted from May to September 2023 and distributed via social and private networks. ResultsThe evaluation of n = 986 questionnaires, mostly from paramedics (44.6%) and physicians with additional training in emergency medicine (19.5%), showed that the regional distribution of triage systems in Germany is heterogeneous. Overall, 71.2% of the participants were familiar with the triage system implemented locally. Within the 12 months before the survey, 41.1% had received specific training on using these algorithms, while 44.0% had not used them at all or only once in an actual medical incident. ConclusionSeven out of ten participants were aware of the locally implemented triage system. This number is considered high in international comparison. The regional distribution of triage systems in Germany is heterogeneous. Establishing a nationally uniform rapid triage system would correspond to international recommendations and was requested by the study participants.

Abstract Objectives A cricothyrotomy represents an emergency procedure that may be considered a last option for securing the airway. While fortunately rare, it is important to note that such invasive procedures must be mastered if they are to be used. Therefore, regular training is essential to gain routine. The aim of the present study was to investigate whether professional groups with different levels of experience with the procedure succeed in learning the procedure with a virtual reality trainer. Materials and methods In a multicenter approach, 146 employees with four different professional backgrounds—otorhinolaryngologists, anesthesiologists, emergency physicians and certified nurses—were included in the study. The participants were required to complete a virtual reality (VR) cricothyrotomy scenario in three consecutive runs, and the time required and errors in the procedure were recorded. The training experience was subsequently evaluated subjectively using a questionnaire. Results The study included 146 participants with an average age of 33 years and an average of 5 years of professional experience. The majority of participants (74%) reported an improvement in the speed of the procedure and in the procedural steps (87%). These subjective improvements were confirmed objectively by the time required for completion of the procedure and the points achieved. Gaming experience had a significant effect on both the score (p = 0.023) and procedure time (p = 0.039), whereas age and medical specialization did not. Real-life experience with cricothyrotomy had no significant effect on performance in VR. Conclusion Virtual reality provides an effective method for training healthcare professionals in cricothyrotomy, regardless of their specialty or prior experience. The participants showed significant improvements in both the speed and accuracy of the procedure after training, regardless of their prior experience or medical background. Further research is necessary to assess the benefits of VR simulation for training cricothyrotomy in real-world procedures. Trial registration DRKS00031736, registered on the 20th of April 2023.

Simulations have become an indispensable part of modern teaching. They provide a safe environment for learning and perfecting complex clinical skills without endangering patients. This article highlights the current possibilities and advantages of simulation in anesthesiology, intensive care medicine, emergency medicine, and pain medicine and shows how these technologies can revolutionize medical education.

Background: The frequency and complexity of crises and disasters are steadily increasing. In Germany, civil protection is organized federally and relies heavily on volunteer engagement. During crises, particularly in critical infrastructures (KRITIS), workload significantly increases. Objective: This study examines the availability of civilian emergency personnel during disasters, focusing especially on individuals with dual roles-such as those employed in KRITIS and volunteering in civil protection-and the impact of dual roles as well as professional and private obligations on operational readiness. Materials and methods: As part of a national online survey conducted between June and October 2024, volunteers from civil protection organizations were contacted. The questionnaire collected demographic data, professional occupation, civil protection engagement, qualifications, working hours, leave options, and availability during deployments. Results: A total of 3681 complete responses were included in the analysis (N = 3681). Of the respondents, 51.6% are employed in a KRITIS sector, and 20.5% hold more than one volunteer position. Among physicians, 32.7% are engaged in more than one volunteer role. In the event of a disaster, 30% of volunteers are always available, 65% are only partially available, and 5% are not available at all. The main reason for unavailability is professional obligations (57.4%), particularly for those employed in KRITIS sectors and for physicians who report a high workload of 49 h per week. Conclusion: The results show that the availability of civilian emergency personnel during disasters is significantly limited by professional and private obligations as well as dual roles. In Germany, only about 671,500 out of 1.7 million (60.5%) people active in disaster management are readily available as volunteers. This issue is particularly acute for those employed in KRITIS sectors and for physicians. Low leave rates and demographic changes further exacerbate the issue. Targeted measures to reduce workload and attract new volunteers are necessary to strengthen the resilience of civil protection.

Modern patient simulation and CRM (crisis resource management) are very often mentioned in the same context. In this article, we will classify the parallel developments of the last 60 years and the introduction of CRM in healthcare concept over 30 years ago and to examine them from different perspectives. CRM has more dimensions than most people realize. This toolbox deals with the description and optimization of human factors in the context of the healthcare system. Since the human factors and the effects on the quality of treatment can be addressed very well in the context of simulation training, they play a natural role in many simulation training courses.

Die Versorgungsqualität bei einem Massenanfall von Notfallpatienten wird entscheidend durch die schnelle Identifikation lebensbedrohlich erkrankter oder verletzter Patienten beeinflusst. Diese soll durch Nutzung von Vorsichtungsalgorithmen (VSA) erleichtert werden. Über die regionale Verteilung und den Bekanntheitsgrad dieser Instrumente in Deutschland liegen bisher keine Erkenntnisse vor. Ziel der vorliegenden Studie war die Bestandsaufnahme der in Deutschland etablierten VSA und deren regionaler Verteilung anhand der Angaben von medizinischem und Rettungsdienst-Fachpersonal. Online-Umfrage im Zeitraum Mai bis September 2023 über soziale und private Netzwerke mittels Fragebogen zu soziodemografischen Daten und Kenntnissen zu verschiedenen VSA sowie deren praktischem Einsatz. Die Auswertung von n = 986 Fragebögen, mehrheitlich von Notfallsanitätern (44,6

Background: Since 2021, international guidelines for cardiopulmonary resuscitation recommend the implementation of so-called "life-saving systems". These systems include smartphone alerting systems (SAS), which enable dispatch centres to alert first responders via smartphone applications, who are in proximity of a suspected out -of -hospital cardiac arrest (OHCA). However, the effect of SAS on survival remains unknown. Aim: The aim is to assess the rate of survival to hospital discharge in adult patients with OHCA not witnessed by emergency medical services (EMS): before and after SAS implementation. Design: Multicentre, prospective, observational, intention -to -treat, pre-post design clinical trial. Population: Adults (aged >= 18 years), OHCA not witnessed by EMS, no traumatic cause for cardiac arrest, cardiopulmonary resuscitation initiated or continued by EMS. Setting: Dispatch -centre -based. Outcomes: Primary: survival to hospital discharge. Secondary: time to first compression, rate of basic life support measures before EMS arrival, rate of patients with shockable rhythm at EMS arrival, Cerebral Performance Category at hospital discharge, and duration of hospital stay. Sample size: Assuming an absolute difference in survival rates to hospital discharge of 4% in the two groups (11% before implementation of the SAS versus 15% after) and 80% power, and a type 1 error rate of 0.05, the required sample size is N = 1,109 patients per group (at least N = 2,218 evaluated patients in total). Conclusions: The HEROES trial will investigate the effects of a SAS on the survival rate after OHCA. Trial registration: German Clinical Trials Register (DRKS, ID: DRKS00032920)

BACKGROUND:Our investigation aimed to determine how the diverse backgrounds and medical specialties of emergency physicians (Eps) influence the accuracy of diagnoses and the subsequent treatment pathways for patients presenting preclinically with MI symptoms. By scrutinizing the relationships between EPs' specialties and their approaches to patient care, we aimed to unveil potential variances in diagnostic accuracy and treatment choices. METHODS:In this retrospective, monocenter cohort study, we leveraged machine learning techniques to analyze a comprehensive dataset of 2328 patients with suspected MI, encompassing preclinical diagnoses, electrocardiogram (ECG) interpretations, and subsequent treatment strategies by attending EPs. RESULTS:We demonstrated that diagnosis and treatment patterns of different specialties were distinct enough, that machine learning (ML) was able to differentiate between specialties (maximum area under the receiver operating characteristic = 0.80 for general medicine and 0.80 for surgery). In our study, internist demonstrated the highest accuracy for preclinical identification of STEMI (0.96) whereas surgeons showed the highest accuracy for identifying NSTEMI. Our findings highlight significant correlations between EP specialties and the accuracy of both preclinical diagnoses and subsequent treatment pathways for patients with suspected MI. CONCLUSIONS:Our results offer valuable insights into how the diverse backgrounds and specialties of EPs can influence the optimization of patient care in emergency settings. Understanding these patterns can help in the development of tailored training programs and protocols to enhance diagnostic accuracy and treatment efficacy in emergency cardiac care, ultimately optimizing patient treatment and improving outcomes.

Zusammenfassung Hintergrund Bei Massenanfällen von Verletzten (MANV) besteht oft ein Missverhältnis zwischen dem Behandlungsbedarf und den verfügbaren Ressourcen. Verschiedene Sichtungssysteme werden präklinisch verwendet, darunter der „tactical Simple Triage and Rapid Treatment“(tacSTART)-Algorithmus, der speziell für Bedrohungslagen entwickelt wurde. Ziel der Arbeit Die Studie untersuchte, ob der tacSTART-Algorithmus von zivilen und militärischen Rettungskräften ohne vorherige Erfahrung mit Sichtungsalgorithmen wirksam genutzt werden kann. Das Weltwirtschaftsforum (WEF) 2020 bot ein optimales Umfeld für diese Untersuchung. Material und Methoden Die Studie wurde während des WEF in Davos durchgeführt und umfasste nichtärztliches und ärztliches Personal von zivilen und militärischen Rettungsdiensten. Die Teilnehmenden erhielten eine Einführung in den tacSTART-Algorithmus und führten insgesamt 2000 Vorsichtungen an Schauspielpatientinnen und -patienten sowie Patientenkarten durch. Ein Online-Fragebogen diente zur Datenerfassung, welche statistisch ausgewertet wurde. Ergebnisse Die Studienergebnisse zeigten, dass der tacSTART-Algorithmus eine hohe Übereinstimmung mit der wahren Vorsichtung erzielte (91,7 %). Es gab keine signifikanten Unterschiede zwischen zivilen und militärischen Rettungskräften. Die Selbsteinschätzung der Teilnehmenden und die Bewertung des Algorithmus waren positiv. Diskussion Die Studienergebnisse unterstützen die Effektivität des tacSTART-Algorithmus als Instrument zur Vorsichtung in MANV-Szenarien. Die Ergebnisse betonen seine Anwendbarkeit für verschiedene Fachkräftegruppen. Die Studie trägt dazu bei, das Verständnis für Sichtungsalgorithmen in Großschadenslagen zu erweitern und die Patientenversorgung zu verbessern. Graphic abstract

Background: The golden hour of trauma denotes the critical first hour after severe injury where timely medical response is crucial, although scientific support for this time frame is inconsistent. This study emphasizes optimizing trauma care by tailoring treatment to the specific injury rather than focusing solely on the speed of treatment. The aim is to document the need for improvement in prehospital trauma care, particularly by the use of blood and coagulation products. Methods: After a pilot study, a purpose-designed online questionnaire targeted at German physicians and rescue service personnel was utilized to collect their views on general trauma care and specifically on the use of blood and coagulation products in prehospital settings. It also assessed the appropriateness of nine specific blood and coagulation products via a 5-point Likert scale. The percentages for each item were calculated for both physicians (n = 110) and rescue service personnel (n = 142) separately as well as an overall score to delineate patterns of agreement or disagreement. Results: The study reached 9837 individuals, whereby 371 initially answered the questionnaire and 252 participants from Germany were finally included in the statistical analysis. The majority of both physicians (89.1%) and rescue service personnel (90.8%) agreed on the need to improve prehospital trauma care, particularly through the use of blood and coagulation products. Specifically, 60.9% of physicians and 83.8% of rescue personnel supported the prehospital administration of these products. Red blood cell concentrates and fibrinogen were notably endorsed, with 76.2% and 67.1% approval, respectively, for their potential to enhance survival in patients with significant blood loss; however, opinions varied on other blood products. Conclusion: The data demonstrated a readiness to change the trauma approach and confirmed that effective options are available. The utilization of certain products is supported by existing research, underlining the need for their practical implementation in preclinical settings. Here, the emphasis shifts from the isolated time components to the quality of care delivered in an optimized time interval. Ideally, timely and high-quality care should complement each other, leveraging all available therapeutic resources. This could lead to the development of a golden approach to trauma to optimize outcomes in trauma care.

Die „Golden Hour of Trauma“ bezeichnet die kritische erste Stunde nach einem schweren Trauma, in der eine rechtzeitige medizinische Versorgung entscheidend ist. Diese Studie fokussiert sich auf die Optimierung der Traumaversorgung durch an die jeweilige Verletzung angepasste Behandlungen statt nur auf die Geschwindigkeit der Versorgung. Ziel war es, den Verbesserungsbedarf der präklinischen Traumaversorgung, insbesondere durch den Einsatz von Blut- und Gerinnungsprodukten, zu erfassen. Ein Online-Fragebogen wurde nach Pilotierung an Ärztinnen und Ärzte sowie Rettungsdienstpersonal gesendet, um deren Einschätzungen zur Traumaversorgung und speziell zur Nutzung von Blutprodukten und Gerinnungspräparaten zu erheben. Die Bewertung von 9 spezifischen Blut- und Gerinnungsprodukten erfolgte mittels einer 5‑stufigen Likert-Skala. Von 9837 erreichten Personen beantworteten 371 den Fragebogen, wobei Daten von 252 Personen in die Analyse einflossen. Die Mehrheit der Ärztinnen und Ärzte (89,1

Background Digitalization in disaster medicine holds significant potential to accelerate rescue operations and ultimately save lives. Mass casualty incidents demand rapid and accurate information management to coordinate effective responses. Currently, first responders manually record triage results on patient cards, and brief information is communicated to the command post via radio communication. Although this process is widely used in practice, it involves several time-consuming and error-prone tasks. To address these issues, we designed, implemented, and evaluated an app-based mobile triage system. This system allows users to document responder details, triage categories, injury patterns, GPS locations, and other important information, which can then be transmitted automatically to the incident commanders. Objective This study aims to design and evaluate an app-based mobile system as a triage and coordination tool for emergency and disaster medicine, comparing its effectiveness with the conventional paper-based system. Methods A total of 38 emergency medicine personnel participated in a within-subject experimental study, completing 2 triage sessions with 30 patient cards each: one session using the app-based mobile system and the other using the paper-based tool. The accuracy of the triages and the time taken for each session were measured. Additionally, we implemented the User Experience Questionnaire along with other items to assess participants’ subjective ratings of the 2 triage tools. Results Our 2 (triage tool) × 2 (tool order) mixed multivariate analysis of variance revealed a significant main effect for the triage tool (P<.001). Post hoc analyses indicated that participants were significantly faster (P<.001) and more accurate (P=.005) in assigning patients to the correct triage category when using the app-based mobile system compared with the paper-based tool. Additionally, analyses showed significantly better subjective ratings for the app-based mobile system compared with the paper-based tool, in terms of both school grading (P<.001) and across all 6 scales of the User Experience Questionnaire (all P<.001). Of the 38 participants, 36 (95%) preferred the app-based mobile system. There was no significant main effect for tool order (P=.24) or session order (P=.06) in our model. Conclusions Our findings demonstrate that the app-based mobile system not only matches the performance of the conventional paper-based tool but may even surpass it in terms of efficiency and usability. This advancement could further enhance the potential of digitalization to optimize processes in disaster medicine, ultimately leading to the possibility of saving more lives.

Pandemien sind unvorhersehbare Ereignisse, die erhebliche Auswirkungen auf die weltweite Gesundheit und Gesellschaft haben können. Sie ereignen sich, wenn ein Pathogen auftritt, gegen das der Mensch keine oder nur eine geringe Immunität besitzt. Planung und Vorbereitung sind wesentliche Schritte, um das Risiko und die Auswirkungen einer Pandemie zu mindern, die Reaktion zu steuern und ein normales Leben wiederherzustellen.

Zusammenfassung Hintergrund Bei Massenanfällen von Verletzten (MANV) besteht oft ein Missverhältnis zwischen dem Behandlungsbedarf und den verfügbaren Ressourcen. Verschiedene Sichtungssysteme werden präklinisch verwendet, darunter der „tactical Simple Triage and Rapid Treatment“(tacSTART)-Algorithmus, der speziell für Bedrohungslagen entwickelt wurde. Ziel der Arbeit Die Studie untersuchte, ob der tacSTART-Algorithmus von zivilen und militärischen Rettungskräften ohne vorherige Erfahrung mit Sichtungsalgorithmen wirksam genutzt werden kann. Das Weltwirtschaftsforum (WEF) 2020 bot ein optimales Umfeld für diese Untersuchung. Material und Methoden Die Studie wurde während des WEF in Davos durchgeführt und umfasste nichtärztliches und ärztliches Personal von zivilen und militärischen Rettungsdiensten. Die Teilnehmenden erhielten eine Einführung in den tacSTART-Algorithmus und führten insgesamt 2000 Vorsichtungen an Schauspielpatientinnen und -patienten sowie Patientenkarten durch. Ein Online-Fragebogen diente zur Datenerfassung, welche statistisch ausgewertet wurde. Ergebnisse Die Studienergebnisse zeigten, dass der tacSTART-Algorithmus eine hohe Übereinstimmung mit der wahren Vorsichtung erzielte (91,7 %). Es gab keine signifikanten Unterschiede zwischen zivilen und militärischen Rettungskräften. Die Selbsteinschätzung der Teilnehmenden und die Bewertung des Algorithmus waren positiv. Diskussion Die Studienergebnisse unterstützen die Effektivität des tacSTART-Algorithmus als Instrument zur Vorsichtung in MANV-Szenarien. Die Ergebnisse betonen seine Anwendbarkeit für verschiedene Fachkräftegruppen. Die Studie trägt dazu bei, das Verständnis für Sichtungsalgorithmen in Großschadenslagen zu erweitern und die Patientenversorgung zu verbessern. Graphic abstract

BACKGROUND:In cases of terrorism, disasters, or mass casualty incidents, far-reaching life-and-death decisions about prioritizing patients are currently made using triage algorithms that focus solely on the patient's current health status rather than their prognosis, thus leaving a fatal gap of patients who are under- or overtriaged. OBJECTIVE:The aim of this proof-of-concept study is to demonstrate a novel approach for triage that no longer classifies patients into triage categories but ranks their urgency according to the anticipated survival time without intervention. Using this approach, we aim to improve the prioritization of casualties by respecting individual injury patterns and vital signs, survival likelihoods, and the availability of rescue resources. METHODS:We designed a mathematical model that allows dynamic simulation of the time course of a patient's vital parameters, depending on individual baseline vital signs and injury severity. The 2 variables were integrated using the well-established Revised Trauma Score (RTS) and the New Injury Severity Score (NISS). An artificial patient database of unique patients with trauma (N=82,277) was then generated and used for analysis of the time course modeling and triage classification. Comparative performance analysis of different triage algorithms was performed. In addition, we applied a sophisticated, state-of-the-art clustering method using the Gower distance to visualize patient cohorts at risk for mistriage. RESULTS:The proposed triage algorithm realistically modeled the time course of a patient's life, depending on injury severity and current vital parameters. Different casualties were ranked by their anticipated time course, reflecting their priority for treatment. Regarding the identification of patients at risk for mistriage, the model outperformed the Simple Triage And Rapid Treatment's triage algorithm but also exclusive stratification by the RTS or the NISS. Multidimensional analysis separated patients with similar patterns of injuries and vital parameters into clusters with different triage classifications. In this large-scale analysis, our algorithm confirmed the previously mentioned conclusions during simulation and descriptive analysis and underlined the significance of this novel approach to triage. CONCLUSIONS:The findings of this study suggest the feasibility and relevance of our model, which is unique in terms of its ranking system, prognosis outline, and time course anticipation. The proposed triage-ranking algorithm could offer an innovative triage method with a wide range of applications in prehospital, disaster, and emergency medicine, as well as simulation and research.

Virtual reality (VR)–based simulation is being increasingly used to train medical students in emergency medicine. However, because the usefulness of VR may depend on various factors, the best practices for implementing this technology in the medical school curriculum are yet to be determined. The overall objective of our study was to assess the perceptions of a large cohort of students toward VR-based training and to identify the associations between these attitudes and individual factors, such as gender and age. The authors implemented a voluntary, VR-based teaching session in the emergency medicine course at the Medical Faculty in Tübingen, Germany. Fourth-year medical students were invited to participate on a voluntary basis. Afterward, we asked the students about their perceptions, collected data on individual factors, and assessed the test scores achieved by them in the VR-based assessment scenarios. We used ordinal regression analysis and linear mixed-effects analysis to detect the impact of individual factors on the questionnaire answers. A total of 129 students participated in our study (mean age 24.7, SD 2.9 years; n=51, 39.8% male; n=77, 60.2% female). No student had previously used VR for learning, and only 4.7% (n=6) of the students had prior experience with VR. Most of the students agreed that VR can convey complex issues quickly (n=117, 91%), that VR is a useful addition to mannequin-based courses (n=114, 88%) or could even replace them (n=93, 72%), and that VR simulations should also be used for examinations (n=103, 80%). However, female students showed significantly less agreement with these statements. Most students perceived the VR scenario as realistic (n=69, 53%) and intuitive (n=62, 48%), with a relatively lower agreement for the latter among female respondents. We found high agreement among all participants (n=88, 69%) for immersion but strong disagreement (n=69, 54%) for empathy with the virtual patient. Only 3% (n=4) of the students felt confident regarding the medical content. Responses for the linguistic aspects of the scenario were largely mixed; however, most of the students were confident with the English language (not native) scenarios and disagreed that the scenario should be offered in their native language (female students agreed more strongly than male students). Most of the students would not have felt confident with the scenarios in a real-world context (n=69, 53%). Although physical symptoms during VR sessions were reported by 16% (n=21) of the respondents, this did not lead to the termination of the simulation. The regression analysis revealed that the final test scores were not influenced by gender, age, or prior experience in emergency medicine or with virtual reality. In this study, we observed a strong positive attitude in medical students toward VR-based teaching and assessment. However, this positivity was comparatively lower among female students, potentially indicating that gender differences need to be addressed when VR is implemented in the curriculum. Interestingly, gender, age, or prior experience did not influence the final test scores. Furthermore, confidence regarding the medical content was low, which suggests that the students may need further training in emergency medicine.

Aim Sudden cardiac arrest is one of the leading causes of death throughout Europe, but despite intensive efforts, the lay resuscitation rate in Germany has been low for years. In this study, the level of knowledge in this area and the willingness of the population to undergo further training were surveyed using Berlin as an example. Methods The study participants were randomly selected. In all, 120 persons aged 40-70 years were enrolled. Knowledge about resuscitation was assessed by a questionnaire with 24 items. In addition, three videos with different situations concerning lay resuscitation were part of the questionnaire. The participants had to answer these questions with the help of six possible answers. One item was also used to assess the willingness to undergo further training on this topic. In order to show possible differences, a group with a first aid course in the past year and a group with a first aid course a long time ago were considered separately. Results Of the participants, 74% (n = 89) fully completed the survey. Of these, 11% (n = 10) had attended a first aid course within the past year. In this group, 90% (n = 9) of participants were confident in their ability to recognize and treat a cardiac arrest, compared with 20.25% (n = 16) in the comparison group with first aid training longer ago, 50% (n = 5) and 11% (n = 9) of the participants were confident to use an automated external defibrillator, and 92% (n = 82) of all participants confirmed their willingness to attend regular first aid training. Conclusion The group with a recent first aid course performed significantly better than the comparison group in terms of knowledge of resuscitation, recognizing, and treating emergency situations. A new approach must be found to close the gaps in knowledge that have been identified. A nationwide course program for all adults in Germany, to be completed annually, could fill this gap quickly and sustainably.