Frontiers in Emergency Medicine (E-Journal)
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Developing a model for predicting intra-abdominal injuries following blunt trauma; a cross-sectional study
Get PDFObjective: Finding the associated factors of traumatic intra-abdominal injuries (IAIs) and designing a predictive model could minimize the unnecessary use of computed tomography (CT) scans. This study aimed to develop a risk stratification model in this regard. Methods: This prospective cross-sectional study was conducted at the emergency department (ED) of a level III trauma center. In this study, we thoroughly examined the association between demographic details, physical examinations, laboratory tests, and ultrasonography with abdominopelvic CT scan results regarding the presence of intra-abdominal injuries following blunt abdominal trauma, trying to develop a risk stratification model in this regard. Result: A total of 472 blunt trauma patients with a mean age of 39.06±18.49 (range: 15-96) were investigated (81.1% male). 47 intraabdominal damages in 45 (9.5%) patients were diagnosed. Based on logistic regression analysis, presence of abdominal pain (odds ratio [OR]: 39.60; 95% CI: 9.42,166.35), positive focused assessment sonography in trauma (FAST results (OR: 46.93; 95% CI: 14079,148.89), and injury severity index (ISS)≥25 (OR: 6.43; 95% CI: 2.07,19.90) were significantly correlated with the presence of intraabdominal injuries in blunt trauma patients. The area under the ROC curve of the model was 0,865 (95% Cl: 0.805,0.926) with 86.67% sensitivity and 86.41% specificity. Conclusion: Being accurate and user-friendly alongside broader criteria compared to similar studies makes our risk stratification model a reliable decision-making tool to optimize CT scan usage in the emergency department
Effectiveness of digital consultation in reducing emergency department length of stay
Get PDFObjective: Emergency department length of stay (EDLOS) is a critical measure of healthcare efficiency and quality, and prolonged stays are associated with worse outcomes, particularly for patients requiring intensive care unit (ICU) admission. This study evaluates the impact of a digital consultation management system implemented at Hiwot Fana Comprehensive University Hospital in Ethiopia between May 2020 and May 2024. Methods: A pre–post quasi-experimental design was utilized to compare EDLOS for ICU patients before and after the implementation of the new consultation system. The traditional consultation process was characterized by multi-step verbal communication among healthcare providers. The new system employed a secure Telegram channel to facilitate real-time communication, whereby all physicians in the consulting service were simultaneously notified of the patient requiring ICU care. We determined the proportion of patients admitted to the ICU staying more than 24 hours in the emergency department (ED) between pre- and post-implementation of the Telegram system using chi-squared tests and mean difference in LOS using Mann Whitney U. Results: This study included 415 patients with 202 patients in the pre-implementation period (May 01, 2020, to May 31, 2022) and 213 in the post-implementation period (June 01, 2022, to May 31, 2024). The mean age was 43.3 years (SD: 18.75 years), and no significant demographic or clinical differences were observed between the pre- and post-intervention groups, except for payment method. Before implementation, 32.6% of patients stayed in the ED> 24 hours while after the implementation 28.8% stayed > 24 hours (P=0.03) The mean EDLOS decreased from 2.83 (SD: 2.5) days to 2.27(SD: 1.64) days following implementation (P=0.04), with a reduction of approximately 13.2 hours in EDLOS. Overall ICU mortality decreased from 31.4% to 25.8%, though this was not statistically significant. Conclusion: A digital consultation system can reduce EDLOS in a limited-income country, consistent with findings from similar studies. Further research is needed to explore long-term impacts and scalability, especially in low-resource settings
New technologies are on our side: Designing AI-Based Protocols for Emergency Departments
No full textAs a nurse in a bustling emergency department (ED), I’ve seen firsthand the chaos and intensity that define our daily work. The constant influx of patients, each with unique needs, creates a high-pressure environment where every second counts. Over the past year, our hospital began integrating artificial intelligence (AI)-based protocols into our workflow, and I’ve witnessed how this technology is reshaping the way we deliver care. It’s been a transformative experience, one that’s brought both promise and challenges, but ultimately, it’s made me hopeful for the future of emergency care
Decision tools for diagnosing spontaneous bacterial peritonitis: a systematic review and meta-analysis
No full textBackgound: Approximately one-third of the spontaneous bacterial peritonitis (SBP) are missed due to the absence of paracentesis, and any delay in antibiotic initiation significantly increases mortality. Clinical decision tools may help to rule out or rule in the diagnosis without paracentesis. This study systematically reviewed the performance of available decision tools for diagnosing SBP in adult patients with cirrhosis. Methods: We included all original studies that evaluated clinical decision tools for SBP diagnosis. Search was conducted in MEDLINE, Embase, Scopus, and Web of Science Core Collection from inception to September 2024. Study quality was evaluated using Quality Assessment of Diagnostic Accuracy Studies version 2 (QUADAS 2). Results: From 2038 records, 44 articles were scrutinized in full text. Twenty-four studies ultimately met eligibility criteria. Most of the studies were at low risk of bias. Several tools relied on laboratory findings with clinical features. In meta-analysis the Mansoura scoring system (cut-off of 4) showed a pooled sensitivity of 70.96% (95% CI: 42.06%,99.86%) and a negative predictive value 92.27% (95% CI: 88.80%,95.74%). The Wehmeyer’s scoring system achieved pooled specificity and positive predictive value of 98.43% (95% CI: 95.29,101.58%) and 90.26% (95% CI: 70.28,110.23%). A MELD score >15 yielded had pooled sensitivity of 83.85% (95% CI: 78.50%,89.20%) and negative predictive value of 87.56% (95% CI: 81.29%,93.84%). Conclusion: Several decision tools, particularly laboratory-based (e.g. procalcitonin) tools, showed high sensitivity to potentially rule out SBP. Some other tools (e.g. Mansoura, Wehmeyer rules) can reliably rule in the diagnosis. However, tools all the tools need further validation before widespread adoption
Bridging performance and practice: the next step for artificial intelligence in basic life support education
No full textRecent studies show that artificial intelligence (AI) has performed well on standardized basic life support (BLS) examinations. King et al. report that GPT-4V achieved 96% and 90% accuracy on the 2016 AHA BLS and advanced cardiac life support (ACLS) exams, respectively, including competent electrocardiograph (ECG) interpretation. This finding reflects substantial progress in multimodal model reasoning and suggests potential use in assessment and personalized learning.
Nevertheless, multiple evaluations of large-language models demonstrate highly variable accuracy in BLS scenarios—ranging from approximately 48% in question-based assessments to 85% in adult cardiac-arrest simulations and poor performance in pediatric and infant cases. Even GPT-4, the most consistent performer (κ ≈ 0.65), exhibits incomplete guideline adherence and limited reliability for unsupervised application. Thus, success in static examinations does not ensure reliable or safe behavior in dynamic clinical settings.
In contrast, Semeraro et al. highlight persistent weaknesses of current multimodal systems such as Qwen 2.5-Max and ChatGPT-4o, whose automatically generated cardiopulmonary resuscitation (CPR) training materials often lack anatomical accuracy, clinical validity, and adherence to professional standards. This discrepancy underscores the translational gap between algorithmic performance and genuine educational reliability.
The broader literature supports that AI, while capable of improving early cardiac arrest detection, compression precision, and feedback interactivity in simulation-based training, still yields inconsistent educational results. These mixed findings indicate that high exam scores do not necessarily guarantee pedagogically sound or clinically applicable training outcomes.
To enable responsible integration of AI in resuscitation education, three priorities should be addressed. First, structured collaboration between AI developers and certified resuscitation educators is required to align algorithmic outputs with American heart association (AHA) and European Resuscitation Council (ERC) standards. Second, expansion of curated, medically verified multimodal datasets—including high-fidelity ECG and procedural imagery—should support model training and validation. Third, independent quality-assurance frameworks are essential to evaluate AI-generated educational content for factual, ethical, and pedagogical integrity before dissemination.
Artificial intelligence demonstrates significant potential to augment BLS education and improve preparedness for cardiac arrest. However, this promise will be realized only through rigorous interdisciplinary oversight, transparent evaluation, and sustained commitment to evidence-based implementation
How does Jordanian patients’ satisfaction with emergency nursing care associated with their knowledge of the triage system and expected time to wait?
Get PDFObjective: Emergency departments (EDs) are critical to healthcare systems, yet in Jordan, overcrowding and resource limitations challenge care quality. This study assessed how Jordanian patient satisfaction with nursing care at EDs related to their understanding of triage systems and wait times. Method: A prospective cross-sectional design was used. Data were collected from largest two healthcare hospitals in Jordan which utilizing Canadian triage system. A convenience sampling method was utilized. All adult patients (≥18 years) were included. However, patient’s triaged at level 1 (resuscitation) or 2 (emergent) based on Canadian triage system, pediatric patients, and/or those with documented history of psychiatric illness were excluded. Valid and reliable tools were used. Result: The mean age of patients was 37.6 years (SD=11.4), with a mean satisfaction score of 15.79/20 (SD=3.22), reflecting high satisfaction. Most patients (61.3%) were unaware of triage processes; however, their satisfaction with nursing care was related with triage understanding (P<0.05). Younger patients (t=2.045, P<0.05), Jordanian nationals (t=1.817, P<0.05), unmarried individuals (F=3.32, P<0.05), and government-sector workers (F=3.42, P< 0.05) reported significantly higher satisfaction than others. Conclusion: Enhancing patient satisfaction in EDs relies on optimizing nursing care, particularly through staff training in triage systems and patient education about triage processes. Implementing standardized protocols, along with accessible educational materials for patients while they are in the waiting room, is critical to addressing care gaps and ensuring sustainable improvements
Beyond the obvious: spontaneous esophageal perforation mimicking flank pain
Get PDFSpontaneous esophageal perforation, also known as Boerhaave syndrome, is a rare but potentially fatal condition that classically presents with chest pain, vomiting, and subcutaneous emphysema. Atypical presentations can lead to diagnostic delays and increased morbidity and mortality rates. A 51-year-old male presented to the emergency department with isolated left flank pain. The CT scan unexpectedly revealed bilateral diffuse subcutaneous emphysema and left pleural effusion. Following chest tube insertion, food particles were recovered from the pleural drainage, which established the diagnosis of esophageal perforation. Emergency surgical repair was performed successfully with a good clinical outcome. This case highlights the importance of maintaining high clinical suspicion for esophageal perforation even in patients presenting with atypical symptoms. The absence of classic triad symptoms should not exclude this diagnosis from consideration. CT imaging can provide crucial diagnostic information when the clinical presentation is unclear or atypical
Evaluation of the severity and pattern of motorcycle-related injuries among riders and passengers in Iran: a retrospective study
Get PDFObjective: Motorcycle-related traffic crashes remain a significant cause of severe injuries and fatalities, particularly in young populations. This study aimed to compare the injury severity and patterns sustained by motorcycle riders and passengers in crashes. Methods: A retrospective analysis was conducted on motorcycle crash victims, including both riders and passengers, evaluated at the forensic medical organization in Iran from 2020 to 2022. Variables such as injury type, helmet use, and demographic factors were compared. The chi-squared test was applied to categorical variables, with P-values of <0.05 considered significant. The injury severity score (ISS) and the abbreviated injury scale (AIS) were used to assess trauma severity. Results: Of 214 cases (81.8% male), helmet use was significantly higher among riders than passengers (39.6% vs. 14.8%, P<0.05). Passengers demonstrated a greater risk of severe injury (45.4%) than riders (27.4%, P=0.01). Head injuries were significantly more prevalent among passengers (13%) than riders (5.7%, P=0.019), correlating with lower helmet use among the passengers. Additionally, fractures and dislocations were more common in passengers, while external injuries predominated in riders. Conclusion: Strengthening helmet regulations for passengers is critical to reducing head trauma. Stricter enforcement of traffic safety measures could significantly mitigate fatalities, especially among novice riders
FEM in 2024, A quick look
Get PDFOver the past year, the journal Frontiers in Emergency Medicine (FEM) has reinforced its dedication to advancing emergency medicine by featuring research from five continents, including Iran, Turkey, India, Ethiopia, Spain, Canada, and the United States. The high volume of submissions reflects growing trust in FEM, though only 20.9% are accepted due to stringent scientific and ethical standards. A major milestone this year was FEM's inclusion in the EBSCO and Magiran databases, increasing visibility. FEM aims to expand publishing opportunities while maintaining quality through expert review. This article highlights key achievements and research contributions from the past year
A 51-year-old man with abdominal pain
No full textSpontaneous isolated celiac artery dissection (SICAD) is a rare vascular condition, often presenting with nonspecific abdominal or flank pain, and may result in downstream visceral ischemia. Early recognition is essential to guide appropriate management. We present a case of SICAD in this report