Archives of Academic Emergency Medicine最新文献

Introduction: Accurate assessment and management of abdominal pain in the emergency department (ED) is crucial, as it can indicate potentially life-threatening conditions requiring timely treatment. This study aimed to evaluate the ability of pain scales to predict critical diagnoses in patients with non-traumatic abdominal pain.

Methods: This cross-sectional study was conducted at a tertiary university hospital and involved individuals aged 15 years and above who presented to the ED with non-traumatic abdominal pain. Pain severity was evaluated using subjective pain scales, including the Numerical Rating Scale (NRS) and the Face Pain Scale (FPS), as well as objective pain scales, including the Critical Care Pain Observation Tool (CPOT) and the Non-verbal Pain Score (NVPS). The area under the receiver operating characteristic curve (AuROC) was employed to determine the discriminative ability of each pain scale to predict critical diagnosis.

Results: 264 cases with the mean age of 47.2±19.4 years were studied (53.0% male). The most common location of abdominal pain was epigastric pain (43.9%). Most patients presented with dull-aching pain, and those with critical diagnoses had more of this characteristic than those with non-critical diagnoses. (52.5% vs. 28.3%, p = 0.01). The overall median NRS, FPS, CPOT, and NVPS of included participants were 8 (interquartile range (IQR) 7-10), 8 (IQR 6-8), 3 (IQR 1-4), and 3 (IQR 2-4), respectively. Patients with critical diagnoses had a higher NVPS score than patients with non-critical diagnoses (median score of 4 vs. 3, p = 0.02). The AuROC of NRS, FPS, CPOT, and NVPS were 0.53 (95% CI: 0.45-0.62), 0.55 (95% CI: 0.46-0.63), 0.59 (95% CI: 0.50-0.68), and 0.62 (95% CI: 0.53-0.71), respectively. The correlation coefficients among these scales were considered moderately correlated or higher.

Conclusion: In evaluating patients with non-traumatic abdominal pain, the NVPS demonstrated the highest accuracy in predicting critical diagnoses. However, all pain scales, whether subjective or objective, exhibited suboptimal performance in predicting critical diagnoses.

Introduction: A range of screening tools has been developed to assist emergency healthcare providers in rapidly and accurately diagnosing strokes. In this study, we investigated the diagnostic value of the Recognition of Stroke in the Emergency Room (ROSIER) scale in identifying individuals with stroke and transient ischemic attack (TIA).

Methods: We conducted a systematic search across online databases of PubMed, Embase, Scopus, and Web of Science until June 12th, 2023, aiming to identify studies that assessed the diagnostic performance of the ROSIER scale in detecting strokes and TIAs among individuals with suspected stroke symptoms.

Results: Data extracted from 34 studies were analyzed, demonstrating that the ROSIER score, with a cut-off value of ≥ 1, has sensitivity of 0.89 (95% confidence interval (CI): 0.86-0.92), specificity of 0.76 (95% CI: 0.69-0.81), diagnostic odds ratio (DOR) of 25.41 (95% CI: 17.2-37.54), and area under the curve (AUC) of 0.91 (95% CI: 0.85-0.90) in detection of strokes and TIAs. Meta-regression subgroup analysis revealed variations in sensitivity and specificity based on different settings and assessors. Sensitivity was higher in pre-hospital settings when the test was administered by emergency medical services (EMS) and emergency department (ED) paramedic staff, whereas specificity was higher in emergency department settings and when physicians and neurologists conducted the test.

Conclusion: A moderate level of evidence shows that the ROSIER scale is considered an excellent tool for identifying strokes and TIAs. As a valid method for identifying strokes, it holds applicability across diverse settings and can be effectively used by assessors with different specialties.

Introduction: Clinical decision tools have been shown to reduce imaging rates for clearance of suspected cervical spine injury (CSI). This review provides more comprehensive evidence on the diagnostic capabilities of National Emergency X-Radiography Utilization Study (NEXUS) and Canadian C-spine rule (CCR) in this regard.

Method: A systematic review of the current literature was performed on studies published until Jan 26^th, 2023, in databases of Medline, Scopus, Web of Science, and Embase, investigating the performance of NEXUS and CCR in blunt trauma patients. QUADAS-2 and GRADE guidelines were used to assess the quality and certainty of evidence. All analyses were performed using the STATA 14.0 statistical analysis software.

Results: 35 articles comprising 70000 patients for NEXUS and 33000 patients for CCR were included in this review. NEXUS and CCR were evaluated to have a sensitivity of 0.94 (95% confidence interval (CI): 0.88 to 0.98) and 1.00 (95% CI: 0.98 to 1.00) in the detection of any CSI and 0.95 (95% CI: 0.89 to 0.98) and 1.00 (95% CI: 0.95 to 1.00) in the detection of clinically important CSI. The area under the curve (AUC) of NEXUS and CCR was 0.85 and 0.97 for any CSI and 0.78 (95% CI: 0.74 to 0.81) and 0.94 (95% CI: 0.91 to 0.96) for clinically important CSI.

Conclusion: Our study demonstrates that both NEXUS and CCR can be used in ruling out patients with low risk of CSI, and CCR was shown to have superior performance. Even though these tools have low specificity, their application can still greatly reduce the number of radiographic imaging performed in emergency departments.

Missed diagnosis of foreign bodies in esophagus occasionally results in adverse consequences for patients. This study aimed to analyze the clinical characteristics of esophageal foreign body missed diagnosis in 12 cases. Among the 12 patients, 7 didn't undergo esophagus-related examination due to mild pain; One case didn't report a clear history of swallowing foreign bodies. For one case, computed tomography (CT) examination had not reached the esophageal foreign body level. Two cases were missed diagnosis because the foreign bodies were too tiny to develop clearly on CT. One case showed foreign body in esophagus during initial CT examination, but after subsequent gastroscopy, no foreign body was found. Among the 12 patients, 7 had esophageal perforation, 1 of which developed a neck abscess, and 1 had peri-esophageal abscess. It seems that, if foreign bodies in the pharynx or esophagus are suspected and no foreign bodies are found in the laryngoscope, chest CT scan is necessary. It is best to perform examination of full-length esophagus and pharynx, because foreign bodies may exist in the post-cricoid region or the deep part of the pyriform sinus, especially in older cases with longer retention times.

Introduction: The leuko-glycemic index (LGI), a combined index of patient leukocyte counts and blood glucose levels, has been shown to predict the prognosis of myocardial infarction (MI) patients. Our study aims to investigate the performance of LGI in prediction of outcomes in a population of diabetic and non-diabetic MI patients.

Methods: This observational registry-based cohort study was performed on acute myocardial infarction (AMI) patients. Participants were sub-grouped according to their diabetes status and the calculated optimal LGI cut-off value. The outcomes of the study were the length of hospital stay, and in-hospital and 30-day mortality.

Results: A total of 296 AMI (112 diabetic and 184 non-diabetic) patients were included in the study. The optimal cut-off value of LGI in the diabetic and non-diabetic groups was calculated as 2970.4 mg/dl.mm³ and 2249.4 mg/dl.mm³, respectively. High LGI was associated with increased hospital admission duration in non-diabetic patients (p = 0.017). The area under the curve (AUC) of LGI for prediction of in-hospital mortality was 0.93 (95% CI: 0.87 to 1.00) in the diabetic group and 0.92 (95% CI: 0.85 to 0.99) in the non-diabetic group. LGI had a sensitivity and specificity of 90.00%, and 93.14% in prediction of in-hospital mortality in the diabetic group compared to 77.77% and 90.85% in the non-diabetic group. We observed 4 post-discharge mortalities in our patient group.

Conclusion: Our study demonstrated that higher LGI predicts in-hospital mortality in both diabetic and non-diabetic patients, while the length of hospital stay was only predicted by LGI levels in non-diabetic patients.

Introduction: In spite of the results of previous studies regarding the benefits of ultrasonography for diagnosis of elbow fractures in children, the exact accuracy of this imaging modality is still under debate. Therefore, in this diagnostic systematic review and meta-analysis, we aimed to investigate the accuracy of ultrasonography in this regard.

Methods: Two independent reviewers performed systematic search in Web of Science, Embase, PubMed, Cochrane, and Scopus for studies published from inception of these databases to May 2023. Quality assessment of the included studies was performed using Quality Assessment Tool for Diagnostic Accuracy Studies (QUADAS-2). Meta-Disc software version 1.4 and Stata statistical software package version 17.0 were used for statistical analysis.

Results: A total of 648 studies with 1000 patients were included in the meta-analysis. The pooled sensitivity and specificity were 0.95 (95% CI: 0.93-0.97) and 0.87 (95% CI: 0.84-0.90), respectively. Pooled positive likelihood ratio (PLR) was 6.71 (95% CI: 3.86-11.67), negative likelihood ratio (NLR) was 0.09 (95% CI: 0.03-0.22), and pooled diagnostic odds ratio (DOR) of ultrasonography in detection of elbow fracture in children was 89.85 (95% CI: 31.56-255.8). The area under the summary receiver operating characteristic (ROC) curve for accuracy of ultrasonography in this regard was 0.93. Egger's and Begg's analyses showed that there is no significant publication bias (P=0.11 and P=0.29, respectively).

Conclusion: Our meta-analysis revealed that ultrasonography is a relatively promising diagnostic imaging modality for identification of elbow fractures in children. However, clinicians employing ultrasonography for diagnosis of elbow fractures should be aware that studies included in this meta-analysis had limitations regarding methodological quality and are subject to risk of bias. Future high-quality studies with standardization of ultrasonography examination protocol are required to thoroughly validate ultrasonography for elbow fractures.

Introduction: Agitation management in delirious patients is crucial in a crowded emergency department (ED) for both patient and personnel safety. Benzodiazepines, antipsychotics, and newly derived ketamine are among the most commonly used drugs in controlling these cases. This study aimed to compare the effectiveness of haloperidol-midazolam with haloperidol-ketamine combination in this regard.

Methods: In this double-blind randomized clinical trial, delirious patients with agitation in ED were randomly assigned to a group: group A: haloperidol 2.5 mg IV and midazolam 0.05 mg/kg IV or group B: haloperidol 2.5 mg IV and ketamine 0.5 mg/kg IV. Sedative effects as well as side effects at 0, 5, 10, 15, 30 minutes and 1, 2, 4 hours after the intervention were compared between the 2 groups.

Results: We enrolled 140 cases with Altered Mental Status Score (AMSS)≥+2 and mean age of 52.819.4 years (78.5% male). Agitation was significantly controlled in both groups (p<0.05). In group B, AMSS score was more significantly and rapidly reduced 5 (p = 0.021), 10 (p = 0.009), and 15 (p = 0.034) minutes after drug administration. After intervention, oxygen saturation was significantly decreased in group A 5 (p = 0.031) and 10 (p = 0.019) minutes after baseline. Time required to the maximum effect was significantly lower in group B versus group A (p=0.014). Less patients in group B had major side effects (p=0.018) and needed physical restraint (p=0.001).

Conclusions: Haloperidol-ketamine can control agitation in delirium more rapidly than haloperidol-midazolam. This combination had lower adverse events with lower need for physical restraint.

Introduction: Artificial Inteligence (AI) application in emergency medicine is subject to ethical and legal inconsistencies. The purposes of this study were to map the extent of AI applications in emergency medicine, to identify ethical issues related to the use of AI, and to propose an ethical framework for its use.

Methods: A comprehensive literature collection was compiled through electronic databases/internet search engines (PubMed, Web of Science Platform, MEDLINE, Scopus, Google Scholar/Academia, and ERIC) and reference lists. We considered studies published between 1 January 2014 and 6 October 2022. Articles that did not self-classify as studies of an AI intervention, those that were not relevant to Emergency Departments (EDs), and articles that did not report outcomes or evaluations were excluded. Descriptive and thematic analyses of data extracted from the included articles were conducted.

Results: A total of 137 out of the 2175 citations in the original database were eligible for full-text evaluation. Of these articles, 47 were included in the scoping review and considered for theme extraction. This review covers seven main areas of AI techniques in emergency medicine: Machine Learning (ML) Algorithms (10.64%), prehospital emergency management (12.76%), triage, patient acuity and disposition of patients (19.15%), disease and condition prediction (23.40%), emergency department management (17.03%), the future impact of AI on Emergency Medical Services (EMS) (8.51%), and ethical issues (8.51%).

Conclusion: There has been a rapid increase in AI research in emergency medicine in recent years. Several studies have demonstrated the potential of AI in diverse contexts, particularly when improving patient outcomes through predictive modelling. According to the synthesis of studies in our review, AI-based decision-making lacks transparency. This feature makes AI decision-making opaque.

Monkeypox is a zoonotic disease caused by a double-stranded DNA virus belonging to the genus Orthopoxvirus. Despite being endemic in Central and West Africa, the disease has received relatively little research attention until recent times. As the Coronavirus disease 2019 (COVID-19) pandemic continues to affect the world, the rising number of monkeypox cases in non-endemic countries has further stoked global public health concerns about another pandemic. Unlike previous outbreaks outside Africa, most patients in the present outbreak had no history of travel to the endemic regions. The overwhelming majority of patients were initially identified amongst homosexual men, who had attended large gatherings. Mutations in the coding regions of the viral genome may have resulted in fitness adaptation, enhancement of immune evasion mechanisms, and more efficient transmissibility of the 2022 monkeypox virus. Multiple factors such as diminished cross-protective herd immunity (cessation of smallpox vaccination), deforestation, civil war, refugee displacement, farming, enhanced global interconnectedness, and even climate change may facilitate the unexpected emergence of the disease. In light of the increasing number of cases reported in the present outbreak, healthcare professionals should update their knowledge about monkeypox disease, including its diagnosis, prevention, and clinical management. Herein, we provide an overview of monkeypox, with a focus on the 2022 outbreak, to serve as a primer for clinical practitioners who may encounter the disease in their practice.