BACKGROUND: Prompt epinephrine administration is important to improve outcomes in anaphylaxis.
OBJECTIVE: The objective of our study was to assess the impact of prehospital epinephrine on clinical outcomes of hospital admission, biphasic reactions, and ED length of stay (LOS) in a cohort of ED anaphylaxis patients including both children and adults.
METHODS: We conducted a single-center prospective and retrospective cohort study of anaphylaxis patients from April 2008 to December 2022. Associations between prehospital epinephrine administration with biphasic reactions and ED LOS were assessed with univariable models and the association with ED disposition was assessed with both univariable and multivariable logistic regression.
RESULTS: A total of 1107 patient visits were included for analysis. The median patient age was 29 (IQR 14-50), 593 (53.6%) patients were female, 366 (33.1%) were under 18 years of age. Patients in the prehospital epinephrine group were also less likely to experience a biphasic reaction (5.4% vs 9.3%; OR 0.56, 95% CI 0.34-0.92) and had a decreased ED LOS (median 4.0 hours vs 4.7 hours). There was no difference in hospital admission between patients with and without prehospital epinephrine in both the univariable (19.5% vs 15.7%; OR 1.30, 95% CI: 0.94-1.79) and multivariable (aOR 1.08, 95% CI: 0.71-1.64) models.
CONCLUSIONS: Prehospital epinephrine administration reduced the odds of a biphasic reaction and decreased ED LOS but did not reduce hospitalization in this cohort of ED anaphylaxis patients. Our findings suggest that timely administration of prehospital epinephrine is associated with improved patient outcomes.

BACKGROUND: The development of emergency department (ED) triage systems remains challenging in accurately differentiating patients with acute abdominal pain (AAP) who are critical and urgent for surgery due to subjectivity and limitations. We use machine learning models to predict emergency surgical abdominal pain patients in triage, and then compare their performance with conventional Logistic regression models.
METHODS: Using 38 214 patients presenting with acute abdominal pain at Zhongnan Hospital of Wuhan University between March 1, 2014, and March 1, 2022, we identified all adult patients (aged ≥18 years). We utilized routinely available triage data in electronic medical records as predictors, including structured data (eg, triage vital signs, gender, and age) and unstructured data (chief complaints and physical examinations in free-text format). The primary outcome measure was whether emergency surgery was performed. The dataset was randomly sampled, with 80% assigned to the training set and 20% to the test set. We developed 5 machine learning models: Light Gradient Boosting Machine (Light GBM), eXtreme Gradient Boosting (XGBoost), Deep Neural Network (DNN), and Random Forest (RF). Logistic regression (LR) served as the reference model. Model performance was calculated for each model, including the area under the receiver-work characteristic curve (AUC) and net benefit (decision curve), as well as the confusion matrix.
RESULTS: Of all the 38 214 acute abdominal pain patients, 4208 underwent emergency abdominal surgery while 34 006 received non-surgical treatment. In the surgery outcome prediction, all 4 machine learning models outperformed the reference model (eg, AUC, 0.899 [95%CI 0.891-0.903] in the Light GBM vs. 0.885 [95%CI 0.876-0.891] in the reference model), Similarly, most machine learning models exhibited significant improvements in net reclassification compared to the reference model (eg, NRIs of 0.0812[95%CI, 0.055-0.1105] in the XGBoost), with the exception of the RF model. Decision curve analysis shows that across the entire range of thresholds, the net benefits of the XGBoost and the Light GBM models were higher than the reference model. In particular, the Light GBM model performed well in predicting the need for emergency abdominal surgery with higher sensitivity, specificity, and accuracy.
CONCLUSIONS: Machine learning models have demonstrated superior performance in predicting emergency abdominal pain surgery compared to traditional models. Modern machine learning improves clinical triage decisions and ensures that critically needy patients receive priority for emergency resources and timely, effective treatment.

BACKGROUND: Cocaine is commonly consumed with ethanol, which leads to the formation of cocaethylene through transesterification. Cocaethylene is an active metabolite of cocaine with a longer duration of action. Literature on the combined toxicity of cocaine, ethanol, and cocaethylene is conflicting. We aimed to compare the acute toxicities of co-exposure to cocaine and ethanol versus cocaine alone in Hong Kong.
METHODS: This was a retrospective study on acute cocaine toxicities reported to the Hong Kong Poison Control Center from 1 January 2010 to 22 January 2023. Cocaine exposure was confirmed by urine immunoassays/laboratory tests and ethanol co-ingestion was confirmed by blood ethanol concentrations. A serious outcome was defined as a National Poison Data System outcome moderate or above. Univariate analyses and multivariable logistic regression were performed to compare the associations of clinical outcomes with and without ethanol, followed by subgroup analyses of cases with complete data.
RESULTS: We analyzed 109 patients (median age 29 years, 71% men, 68% Chinese), of whom 20 had confirmed ethanol co-ingestion (mean blood ethanol concentration 1350 mg/L). Multivariable analysis showed that co-exposure to cocaine and ethanol was associated with a lower risk of serious outcomes (adjusted odds ratio 0.09, 95% confidence interval 0.01-0.77; p = 0.03) after adjusting for age, sex, ethnicity, route of cocaine administration, and physical health status. Subgroup analyses showed similar findings.
CONCLUSIONS: In contrast to previous studies, we did not identify a higher risk of serious outcomes after co-exposure to cocaine and ethanol compared to cocaine alone in a predominantly Chinese cohort.

BACKGROUND: This study aimed to evaluate the discriminatory performance of 11 vital sign-based early warning scores (EWSs) and three shock indices in early sepsis prediction in the emergency department (ED).
METHODS: We performed a retrospective study on consecutive adult patients with an infection over 3 months in a public ED in Hong Kong. The primary outcome was sepsis (Sepsis-3 definition) within 48 h of ED presentation. Using c-statistics and the DeLong test, we compared 11 EWSs, including the National Early Warning Score 2 (NEWS2), Modified Early Warning Score, and Worthing Physiological Scoring System (WPS), etc., and three shock indices (the shock index [SI], modified shock index [MSI], and diastolic shock index [DSI]), with Systemic Inflammatory Response Syndrome (SIRS) and quick Sequential Organ Failure Assessment (qSOFA) in predicting the primary outcome, intensive care unit admission, and mortality at different time points.
RESULTS: We analyzed 601 patients, of whom 166 (27.6%) developed sepsis. NEWS2 had the highest point estimate (area under the receiver operating characteristic curve [AUROC] 0.75, 95%CI 0.70-0.79) and was significantly better than SIRS, qSOFA, other EWSs and shock indices, except WPS, at predicting the primary outcome. However, the pooled sensitivity and specificity of NEWS2 ≥ 5 for the prediction of sepsis were 0.45 (95%CI 0.37-0.52) and 0.88 (95%CI 0.85-0.91), respectively. The discriminatory performance of all EWSs and shock indices declined when used to predict mortality at a more remote time point.
CONCLUSIONS: NEWS2 compared favorably with other EWSs and shock indices in early sepsis prediction but its low sensitivity at the usual cut-off point requires further modification for sepsis screening.

UNASSIGNED: The objective of this study was to investigate latent classes of oral health and the factors associated with them in acutely admitted elderly inpatients.
UNASSIGNED: A cross-sectional study was conducted using purposive sampling to survey Chinese older-adult acutely inpatients. Data was collected utilizing several instruments, including a general information questionnaire, Brief Oral Health Status Examination (BOHSE), Oral Frailty Index-8 (OFI-8), Mini-Nutritional Assessment Short Form (MNA-SF), and Frailty Screening Questionnaire (FSQ). Latent class analysis was applied to identify distinct categories of oral health among elderly inpatients, and multinomial logistic regression was employed to analyze the factors associated with different oral health categories.
UNASSIGNED: In this study, a total of 504 elderly patients were ultimately included, leading to the identification of three latent classes of oral health: \"oral health-low level group (41.27%)\", \"oral health-moderate level group (25.4%)\", and \"oral health-high level group (33.33%)\". The findings revealed that patients with advanced age, elevated neutrophil percentage, and higher C-reactive protein (CRP) values were more likely to be classified in the low oral health group. Additionally, individuals experiencing malnutrition and frailty had a higher risk of falling into the low oral health category. Those with comorbidities and oral frailty were more prevalent in the moderate oral health group. At the same time, elderly patients with higher BMI (22.95±3.043) ratios were more likely to be categorized in the high oral health group.
UNASSIGNED: This study sheds light on three distinct latent classes of oral health among acutely admitted elderly inpatients. These findings underscore the importance of healthcare professionals focusing on the assessment and health education of elderly patients\' oral health. Furthermore, personalized interventions should be developed to promote healthy aging, with particularly attention to enhancing oral health outcomes in this population.

Hearing difficulty (HD) may be associated with an increased frequency of emergency department (ED) visits among older adults. The COVID-19 pandemic has adversely affected the health of older adults. However, less is known about the characteristics of ED visits by older adults with HD during the pandemic. This study examines the association between self-reported HD severity and ED visits during the pandemic. This population-based cross-sectional study used self-reported data on HD and the characteristics of respondents aged 65 years or older from three cycles of the National Health Interview Survey from 2020 to 2022. Data were analysed from February 23, 2023, to March 22, 2023. The primary outcome was self-reported ED visits in the past 12 months. This study employed generalised linear models to examine the relationship between ED visits (dependent variable) and HD in older adults, and the effect sizes were expressed as rate ratios. Key independent variables included the reasons for ED visit. Covariates such as demographic characteristics and socio-economic status were controlled for to account for potential confounding effects. During the pandemic, older adults with HD commonly visited the ED because of chronic pain (82.8%), frailty (77.9%), trouble falling/staying asleep (73.2%), hypertension (67.4%), and arthritis (60.1%), all of which were 1.5-times more likely in these adults than in those with normal hearing (chronic pain: adjusted rate ratio [ARR], 1.64 [95% CI 1.44-1.93]; frailty: ARR, 1.57 [95% CI 1.16-1.87]; trouble falling/staying asleep: ARR, 1.51 [95% CI 1.21-1.82]; hypertension: ARR, 1.01 [95% CI 0.92-1.23]; arthritis: ARR, 1.39 [95% CI 1.31-1.57]. Older adults with HD were more likely to visit the ED for chronic pain, frailty, trouble falling/staying asleep, hypertension, and arthritis than those with normal hearing during the COVID-19 pandemic. Our findings will be help for healthcare providers to be aware of these potential barriers and to implement strategies to ensure that patients with hearing difficulties can access necessary emergency care effectively.

OBJECTIVE: This study aims to explore the impact of emergency department internships on the attitudes towards death among undergraduate nursing students and their preferences for end-of-life care settings. Additionally, the study analyzes the reasons behind nursing students\' choices of end-of-life care settings and provides insights for improving undergraduate education on attitudes towards death and end-of-life care, and provide reference for the development of emergency hospice care.
METHODS: This study adopts an observational design with a self-controlled before-and-after approach.
METHODS: A questionnaire survey was conducted with 96 nursing interns between July 2021 to June 2022. Demographic information and data on attitudes towards death, and preferences for end-oflife care location were collected by online questionnaire. Paired test were conducted to compare differences between groups.
RESULTS: The study included a total of 96 nursing students with an average age of 21.11 years. The scores for the avoidance-acceptance dimension of death attitudes before and after the internship were 2.40 (1.80, 3.00) and 2.20 (1.60, 3.00), respectively, showing a significant difference (Z = -2.084, p = 0.037). Factors such as gender, experience in caring for critically ill or dying patients, knowledge of death education, and discussions about death at home were found to influence nursing students\' attitudes towards death. Nursing students expressed a preference for receiving end-of-life care and treatment in their homes or in hospice/palliative care wards, while the intensive care unit, emergency department, and nursing homes were the least preferred settings. There were significant differences in nursing students\' preferences for end-of-life care settings before and after the internship (p = 0.000). Importantly, the number of nursing students expressing a desire to receive end-of-life care in the emergency department increased from 2 to 7 after the internship, while the number of students not wanting end-of-life care in the emergency department decreased by 5.

BACKGROUND: While the number of emergency patients worldwide continues to increase, emergency doctors often face moral distress. It hampers the overall efficiency of the emergency department, even leading to a reduction in human resources.
OBJECTIVE: This study explored the experience of moral distress among emergency department doctors and analyzed the causes of its occurrence and the strategies for addressing it.
METHODS: Purposive and snowball sampling strategies were used in this study. Data were collected through in-depth, semi-structured interviews with 10 doctors working in the emergency department of a tertiary general hospital in southwest China. The interview data underwent processing using the Nvivo 14 software. The data analysis was guided by Colaizzi\'s phenomenological analysis method.
RESULTS: This study yielded five themes: (1) imbalance between Limited Medical Resources and High-Quality Treatment Needs; (2) Ineffective Communication with Patients; (3) Rescuing Patients With no prospect of treatment; (4) Challenges in Sustaining Optimal Treatment Measures; and (5) Strategies for Addressing Moral Distress.
CONCLUSIONS: The moral distress faced by emergency doctors stems from various aspects. Clinical management and policymakers can alleviate this distress by enhancing the dissemination of emergency medical knowledge to the general public, improving the social and economic support systems, and strengthening multidisciplinary collaboration and doctors\' communication skills.

UNASSIGNED: Rapid and accurate diagnosis of the causative agents is essential for clinical management of bloodstream infections (BSIs) that might induce sepsis/septic shock. A considerable number of suspected sepsis patients initially enter the health-care system through an emergency department (ED), hence it is vital to establish an early strategy to recognize sepsis and initiate prompt care in ED. This study aimed to evaluate the diagnostic performance and clinical value of droplet digital PCR (ddPCR) assay in suspected sepsis patients in the ED.
UNASSIGNED: This was a prospective single-centered observational study including patients admitted to the ED from 25 October 2022 to 3 June 2023 with suspected BSIs screened by Modified Shapiro Score (MSS) score. The comparison between ddPCR and blood culture (BC) was performed to evaluate the diagnostic performance of ddPCR for BSIs. Meanwhile, correlative analysis between ddPCR and the inflammatory and prognostic-related biomarkers were conducted to explore the relevance. Further, the health economic evaluation of the ddPCR was analyzed.
UNASSIGNED: 258 samples from 228 patients, with BC and ddPCR performed simultaneously, were included in this study. We found that ddPCR results were positive in 48.13% (103 of 214) of episodes, with identification of 132 pathogens. In contrast, BC only detected 18 positives, 88.89% of which were identified by ddPCR. When considering culture-proven BSIs, ddPCR shows an overall sensitivity of 88.89% and specificity of 55.61%, the optimal diagnostic power for quantifying BSI through ddPCR is achieved with a copy cutoff of 155.5. We further found that ddPCR exhibited a high accuracy especially in liver abscess patients. Among all the identified virus by ddPCR, EBV has a substantially higher positive rate with a link to immunosuppression. Moreover, the copies of pathogens in ddPCR were positively correlated with various markers of inflammation, coagulation, immunity as well as prognosis. With high sensitivity and specificity, ddPCR facilitates precision antimicrobial stewardship and reduces health care costs.
UNASSIGNED: The multiplexed ddPCR delivers precise and quantitative load data on the causal pathogen, offers the ability to monitor the patient\'s condition and may serve as early warning of sepsis in time-urgent clinical situations as ED.
UNASSIGNED: Early detection and effective administration of antibiotics are essential to improve clinical outcomes for those with life-threatening infection in the emergency department. ddPCR, an emerging tool for rapid and sensitive pathogen identification used as a precise bedside test, has developed to address the current challenges of BSI diagnosis and precise treatment. It characterizes sensitivity, specificity, reproducibility, and absolute quantifications without a standard curve. ddPCR can detect causative pathogens and related resistance genes in patients with suspected BSIs within a span of three hours. In addition, it can identify polymicrobial BSIs and dynamically monitor changes in pathogenic microorganisms in the blood and can be used to evaluate antibiotic efficacy and survival prognosis. Moreover, the copies of pathogens in ddPCR were positively correlated with various markers of inflammation, coagulation, immunity. With high sensitivity and specificity, ddPCR facilitates precision antimicrobial stewardship and reduces health care costs.

UNASSIGNED: To analyze the risk factors associated with intubated critically ill patients in the emergency department (ED) and develop a prediction model by machine learning algorithms.
UNASSIGNED: This study was conducted in an academic tertiary hospital in Hangzhou, China. Critically ill patients admitted to the ED were retrospectively analyzed from May 2018 to July 2022. The demographic characteristics, distribution of organ dysfunction, parameters for different organs\' examination, and status of mechanical ventilation were recorded. These patients were assigned to the intubation and non-intubation groups according to ventilation support. We used the eXtreme Gradient Boosting (XGBoost) algorithm to develop the prediction model and compared it with other algorithms, such as logistic regression, artificial neural network, and random forest. SHapley Additive exPlanations was used to analyze the risk factors of intubated critically ill patients in the ED.
UNASSIGNED: Of 14,589 critically ill patients, 10,212 comprised the training group and 4377 comprised the test group; 2289 intubated patients were obtained from the electronic medical records. The mean age, mean scores of vital signs, parameters of different organs, and blood oxygen examination results differed significantly between the two groups (p < 0.05). The white blood cell count, international normalized ratio, respiratory rate, and pH are the top four risk factors for intubation in critically ill patients. Based on the risk factors in different predictive models, the XGBoost model showed the highest area under the receiver operating characteristic curve (0.84) for predicting ED intubation.
UNASSIGNED: For critically ill patients in the ED, the proposed model can predict potential intubation based on the risk factors in the clinically predictive model.