Emergency Medicine International最新文献

Background and objectives: Diagnosis of multisystem inflammatory syndrome in children (MIS-C) is challenging due to symptom overlap with other common conditions. The primary objective of this multicenter study was to establish normative laboratory values in MIS-C patients and compare to patients evaluated for MIS-C who had other final diagnoses.

Methods: Five hospitals reviewed records of a cohort of patients 6 months to 18 years old who were evaluated for MIS-C between March 31^st 2020 and February 1^st 2022. Patient demographics, clinical presentation, and laboratory values were compared in patients with a final diagnosis of MIS-C versus all other conditions. Patients' final diagnoses and laboratory values for each diagnosis were reported.

Results: Of the 1319 patients that were evaluated for MIS-C at presentation, 293 (22.2%) received a final diagnosis of MIS-C. MIS-C patients had statistically significant differences in laboratory values including D-dimer, ferritin, fibrinogen, troponin, and brain natriuretic peptide when compared to patients evaluated for MIS-C but subsequently diagnosed with other conditions. The most common non-MIS-C diagnoses within this cohort were viral illnesses (26.7%), acute COVID-19 (12.0%), pyelonephritis (6.4%), fever of unknown origin (4.9%), pneumonia (4.7%), gastroenteritis (4.7%), Kawasaki disease (3.7%), other bacterial infections, (3.1%), rheumatologic conditions (3.1%), and sepsis (2.8%).

Conclusions: Many patients who underwent laboratory evaluation for MIS-C during the COVID-19 pandemic received a final diagnosis other than MIS-C. These data may aid pediatricians in differentiating between MIS-C and other febrile conditions as well as reduce unnecessary testing.

Objective: To evaluate the surgical outcomes of microsurgical treatment and transarterial endovascular embolization for dural arteriovenous fistulas (DAVFs).

Methods: A retrospective analysis was conducted on 47 patients diagnosed with high-grade DAVFs (Cognard types 2b, 2a + b, 3, 4, and 5) between June 2019 and June 2022 at Nanjing Brain Hospital, affiliated with Nanjing Medical University. These patients underwent either microsurgery or endovascular embolization. Postoperative efficacy, surgical complications, and related prognostic factors were compared between the two groups. The primary endpoint was a postoperative modified Rankin Scale (mRS) score > 3. Secondary outcomes included angiographic confirmation of fistula occlusion, complication rates, and neurological deficits.

Results: In the microsurgical treatment group, complete fistula occlusion was achieved in 23 patients (85.185%), while 12 patients (60.000%) in the transarterial embolization group (single-session treatment) achieved complete occlusion. Although microsurgical treatment demonstrated a higher occlusion rate, this difference did not reach statistical significance (p=0.051). The median follow-up duration for all patients was 12 months (IQR 1-38 months). During follow-up, 2 patients (4.255%) with residual untreated fistulas developed severe neurological deficits. In contrast, none of the patients with single fistulas developed severe postoperative complications.

Conclusion: Microsurgical treatment demonstrated a higher rate of complete fistula occlusion compared to single-session transarterial embolization in patients with DAVFs, although this difference was not statistically significant. Both treatment modalities showed acceptable safety profiles. Patients with single fistulas showed a lower risk of severe postoperative neurological deficits compared to those with multiple fistulas. This study provides important insights into the emergency treatment of DAVF.

Trial registration: Chinese Registry of Clinical Trials: ChiCTR2300072890.

Purpose: To differentiate complicated appendicitis (CA) from uncomplicated appendicitis (UA) in children, we developed and validated an artificial intelligence (AI) model using a multimodal approach integrating ultrasound images and clinical data.

Methods: A retrospective analysis was performed on 372 pathologically confirmed pediatric appendicitis cases (230 male, 142 female) from three centers, all with preoperative abdominal ultrasound. Deep learning (DL) features and radiomic features were extracted from appendiceal ultrasound images using deep transfer learning (DTL) and conventional radiomic methods, respectively. We selected 12 radiomic features, 9 DL features, and 3 clinical features-namely, white blood cell count (WBC), neutrophil count (NEU), and C-reactive protein (CRP)-for building the machine learning classification model. Based on these features, four distinct models were constructed: the Rad model (radiomic features only), the DL model (DL features only), the DTL model (combined radiomic and DL features), and the Combine model (integrating all three feature types: radiomic, DL, and clinical features). Model performance was evaluated using receiver operating characteristic (ROC) curves, decision curve analysis (DCA), and the DeLong test. Finally, the combined model was compared to the performance of clinicians with varying levels of experience.

Results: The combined model demonstrated consistently favorable performance across all cohorts (AUC: 0.940, 0.895, 0.866, and 0.783 for training and validation sets, respectively). The model's accuracy (0.862) and positive predictive value (0.896) were comparable to senior surgeons (0.741, 0.970) and superior to junior surgeons (0.672, 0.865) in the internal validation cohort. DCA confirmed the clinical utility of the combined model over conventional strategies.

Conclusion: Our ultrasound-based AI model provides reliable differentiation between CA and UA in children, offering potential value as a diagnostic support tool for clinical decision making.

Background: Acute coronary syndrome (ACS) poses a significant burden worldwide; however, the development of high-sensitivity cardiac troponin (hs-cTn) assays has greatly improved patient management by enabling the detection of very low levels of troponin. The objective of this review was to identify current hs-cTn point-of-care (POC) assays, describe their key features, and discuss their analytical and clinical performance.

Methods: PubMed, MEDLINE, and Embase databases, as well as relevant web sources, were searched for publications up to April 10, 2025. The references included describe the main characteristics of POC hs-cTn assays and their companion instruments, as well as studies assessing their analytical or clinical performance in the context of acute myocardial infarction diagnosis.

Results: In addition to information publicly available from the web, 27 publications were considered relevant for this review. From the retrieved sources, seven POC hs-cTn assays were identified as currently cleared by the United States Food and Drug Administration or CE-marked. Four additional POC hs-cTn assays, each evaluated for analytical or clinical performance, were identified as currently or previously under development. POC instruments differ in their key characteristics, many of which are crucial for ensuring their suitability in specific clinical settings and intended applications. Despite some variability in performance across different platforms, they are generally consistent with the high-sensitivity profile expected of cTn assays. Clinical performance indicators for hs-cTn assays align with European Society of Cardiology (ESC) recommendations, particularly when ESC-recommended diagnostic algorithms are applied. Reported sensitivity and negative predictive values exceed 99%, while positive predictive values are above 70%. Moreover, comparative studies of POC hs-cTn assays and laboratory-based hs-cTn tests have demonstrated no significant differences in diagnostic accuracy for ruling in or ruling out acute myocardial infarction.

Conclusion: POC hs-cTn assays represent a promising alternative to traditional laboratory testing, providing similar analytical and clinical performance while enabling faster diagnosis and management of ACS. Expanded use of hs-cTn assays in clinical practice could transform patient care pathways, especially in time-critical situations. Continued research and ongoing technological advancements are critical to ensure optimal use and widespread adoption in routine clinical settings.

Introduction: Gastrointestinal system (GIS) bleeding is one of the most common reasons for emergency department visits. The aim of this study is to investigate the impact of base excess, lactate, and alactic base excess-parameters that can be quickly assessed through blood gas analysis-on predicting the clinical outcome in patients presenting to the emergency department with GIS bleeding.

Materials and methods: The study was retrospective and conducted at a single center from January 1 to December 31, 2022. The collected data included age, gender, blood gas (lactate and base excess), and outcomes (discharge, intensive care, and death).

Results and conclusions: The study included 205 patients (135 males and 70 females). Deceased individuals had a lower average base excess and higher lactate levels. There were no significant differences in ward admission based on alactic base excess status. A base excess cutoff value of ≥ -0.65 was used to predict ward admission, yielding a sensitivity of 57.71%, specificity of 63.33%, PPV of 90.18%, and negative predictive value of 20.43%. According to the data obtained in our study, we observed that a lactate cutoff value ≥ 2.07 could be effective in predicting ICU admission for patients. We also found that a base excess cutoff value ≥ -0.65 could be effective in predicting admission to the ward. The mean base excess was lower in patients who resulted in death compared to survivors, while the mean lactate level was higher. However, no significant result was found regarding alactic base excess.

Objective: To identify patients with sepsis-associated acute kidney injury (SA-AKI) at high risk of respiratory failure within 48 h of admission and enable timely intervention to improve patient prognosis.

Methods: Data from SA-AKI patients admitted to Dongyang People's Hospital between June 2012 and October 2024 were collected, including gender, age, and blood biochemical indicators at admission. Patients were randomly divided into training and validation groups. Independent risk factors for respiratory failure were identified in the training group, and a nomogram prediction model was developed. The model's discriminative ability was assessed using the area under the receiver operating characteristic (ROC) curve (AUC), and its calibration was evaluated using the GiViTi calibration plot. Clinical effectiveness was examined using decision curve analysis (DCA). Cross-validation was performed to test the model's stability using kappa value. The model was subsequently validated in the validation group. Sequential Organ Failure Assessment (SOFA)-based, National Early Warning Score (NEWS)-based, and various other machine learning models were also established and compared with the proposed model using DeLong's test after Bonferroni correction.

Results: A total of 702 patients were included in the study. Independent risk factors for respiratory failure included D-dimer, lactate, pro-BNP, albumin, globulin, transcutaneous blood oxygen saturation, and pulmonary infection. The AUC values for the training and validation groups were 0.818 and 0.795, respectively, with calibration plot p values of 0.973 and 0.864. The DCA curves for both groups indicated superior clinical utility compared with extreme scenarios. This model owned a kappa value of 0.628, indicating for good stability. The SOFA model achieved AUC values of 0.583 (training group) and 0.763 (validation group), while the NEWS model had AUC values of 0.628 (training) and 0.618 (validation). DeLong's test confirmed that the proposed model outperformed SOFA and NEWS models (p < 0.05). In the validation group, the AUC values for SVM, C5.0, XGBoost, and integrated models were 0.781, 0.757, 0.759, and 0.778, respectively, with comparable discriminative ability to the nomogram (p > 0.05).

Conclusion: The nomogram developed in this study based on D-dimer, lactate, pro-BNP, albumin, globulin, transcutaneous blood oxygen saturation, and pulmonary infection was found to effectively predict respiratory failure risk in SA-AKI patients within 48 h of admission.

Objective: To explore evidence relating to the airway management (ranging from observation to intubation) of patients presenting to the emergency department with drug overdose and decreased consciousness.

Introduction: Recreational and prescription drug overdoses are a common reason for patients to present to the emergency department. Patients often have a reduced level of consciousness due to the effects of the drugs involved. There are no evidence-based guidelines identifying which patients can be safely observed, compared with those requiring advanced airway management such as intubation.

Inclusion criteria: Adult patients presenting to the emergency department with drug overdose (recreational drugs, e.g., gamma-hydroxybutyrate and alcohol, and prescription drugs, e.g., benzodiazepines and opioids). Management strategies from intubation (e.g., rapid sequence intubation, emergency airway management) to observation/no intubation (e.g., high flow nasal oxygen, observation, monitoring, recovery position) were included. Studies are needed to describe an approach to airway management in overdose patients with decreased consciousness, which included all primary research. Outcomes included predictors of intubation, mortality, hospital admission, length of stay and complications.

Methods: With the assistance of a Systematic Review Accelerator, we searched PubMed, Cochrane CENTRAL and Embase. Databases were searched from inception to 2^nd April 2024, with no publication language restrictions. We additionally conducted a backward and forward citation search.

Results: Forty-five studies were included (one randomised controlled trial, 14 prospective observational studies, 25 retrospective observational studies and five with other methodology). Four major narrative themes were identified: (1) risk stratifying the decision to intubate; (2) noninvasive monitoring of the patient with overdose; (3) scoring systems predicting the need to intubate; (4) targeted gamma-hydroxybutyrate-specific literature.

Conclusions: Literature on the airway management of emergency department patients with overdose and decreased level of consciousness provides mostly low-quality evidence, with only one RCT. Further higher-level research and evidence are required.

Background: An electrocardiogram is a diagrammatic representation of a heart's electrical activity. This technique can detect life-threatening conditions within minutes. It is one of the major investigative modalities at which emergency physicians should be accurate. The accuracy of emergency residents varies from country to country, with improvement in interpretation as the year of residency increases. There have been no published papers on ECG interpretation among emergency residents until now, but studies on graduating medical students have shown low competency. Methods: A cross-sectional study was conducted on emergency and critical care medicine residents of Tikur Anbessa Specialized Hospital and Saint Paul Millennium Medical College. Data were collected from April 2021 to September 2021 via a structured questionnaire. The data were entered, cleaned, edited, and analyzed via SPSS Version 26.0 statistical analysis software. Descriptive statistics and bivariate and multivariate binary logistic regressions were used to analyze the data. Results: Fifty-seven emergency and critical care medicine residents were able to participate in this study, 33 (57.9%) of whom were from Addis Ababa University and 24 (42.1%) of whom were from Saint Paul Millennium Medical College. The average percentage of EMCC residents who interpreted the ECGs was 29.5%. Only 10 residents (17%) were able to correctly interpret > 50% of the ECGs. Most of the residents who participated in this study were Year 1 residents, followed by Year 2 residents. Among the 15 ECG abnormalities, the commonly identified were polymorphic ventricular tachycardia, normal sinus rhythm, and a double-chamber pacemaker. The year of residency (AOR 3.34) was found to be significantly associated with greater performance in ECG interpretation. Conclusion: According to this study, the interpretation accuracy of ECGs by emergency medicine and critical care residents is low, which is comparable to the findings of studies performed in South Africa and Australia.

Following an administered shock in cardiac arrest, the heart commonly experiences a short phase of inability to efficiently perfuse. Despite being a commonly used feature in the ICD population, postshock pacing (PSP) is yet to be adequately explored for its utility in this pulseless phase. Notably, an overwhelming proportion of available data for transcutaneous pacing in spontaneous cardiac arrest stem from the 1980s and 1990s and revolve largely around nonshockable, as opposed to shockable rhythms. The lack of large-scale clinical trials assessing the efficacy of transcutaneous PSP and the considerable advancements in technology and training facilities since the 1990s indicates a need for reevaluation of current understanding of PSP and its applicability in cardiac arrest. Shedding light into the possible implications of transcutaneous PSP in emergency setting cardiac arrest may not only reshape the current protocols of ALS but also carry the potential of improving survival rates. This concise review serves as a summary of the existing knowledge on the subject of PSP and reveals further possible directions for the development of this therapy.

Background: To determine whether early dynamic changes in the systemic immune-inflammation index (SII) improve prediction of acute kidney injury (AKI) and 1-year mortality in critically ill patients. Methods: In this retrospective cohort study of 17,491 ICU admissions from the MIMIC-IV database, we calculated three SII metrics within the first 24 h of ICU stay: the 24-h SII_slope and the extreme values (SII_min, SII_max). LASSO-selected multivariable logistic regression was used to predict AKI, and Cox proportional hazards models assessed associations with 1-year mortality. A prognostic nomogram integrating SOFA score, APS III score, and log-transformed SII_min and SII_max was developed using the rms package in R. Model performance was evaluated by AUC of ROC curves, calibration plots, decision curve analysis (DCA), and Kaplan-Meier survival curves stratified by SII quartiles. Results: The LASSO-based logistic model identified a steeper 24-h SII_slope as an independent predictor of AKI (AUC 0.739; patients who developed AKI had significantly higher predicted risk than those who did not). Higher SII_min and SII_max were each associated with reduced 1-year survival (log-rank p=0.047 for SII_min quartiles). The nomogram for 1-year mortality demonstrated excellent discrimination (AUC 0.823) and good calibration, and DCA confirmed its clinical utility. Conclusions: Early dynamic changes in SII-especially the 24-h slope-and the first-day SII extremes independently predict AKI and long-term mortality in ICU patients. A nomogram combining SII metrics with standard severity scores may facilitate individualized risk stratification in critical care.