World journal of emergency medicine最新文献

Background: Patients with diabetes mellitus (DM) are vulnerable to community-acquired pneumonia (CAP), which have a high mortality rate. We aimed to investigate the value of heparin-binding protein (HBP) as a prognostic marker of mortality in patients with DM and CAP.

Methods: This retrospective study included CAP patients who were tested for HBP at intensive care unit (ICU) admission from January 2019 to April 2020. Patients were allocated to the DM or non-DM group and paired with propensity score matching. Baseline characteristics and clinical outcomes up to 90 days were evaluated. The primary outcome was the 10-day mortality. Receiver operating characteristic (ROC) curves, Kaplan-Meier analysis, and Cox regression were used for statistical analysis.

Results: Among 152 enrolled patients, 60 pairs were successfully matched. There was no significant difference in 10-day mortality, while more patients in the DM group died within 28 d (P=0.024) and 90 d (P=0.008). In the DM group, HBP levels at ICU admission were higher in 10-day non-survivors than in 10-day survivors (median 182.21 [IQR: 55.43-300] ng/ml vs. median 66.40 [IQR: 34.13-107.85] ng/mL, P=0.019), and HBP levels could predict the 10-day mortality with an area under the ROC curve of 0.747. The cut-off value, sensitivity, and specificity were 160.6 ng/mL, 66.7%, and 90.2%, respectively. Multivariate Cox regression analysis indicated that HBP was an independent prognostic factor for 10-day (HR 7.196, 95%CI: 1.596-32.455, P=0.01), 28-day (HR 4.381, 95%CI: 1.449-13.245, P=0.009), and 90-day mortality (HR 4.581, 95%CI: 1.637-12.819, P=0.004) in patients with DM.

Conclusion: Plasma HBP at ICU admission was associated with the 10-day, 28-day, and 90-day mortality, and might be a prognostic factor in patients with DM and CAP.

Background: Sepsis is one of the main causes of mortality in intensive care units (ICUs). Early prediction is critical for reducing injury. As approximately 36% of sepsis occur within 24 h after emergency department (ED) admission in Medical Information Mart for Intensive Care (MIMIC-IV), a prediction system for the ED triage stage would be helpful. Previous methods such as the quick Sequential Organ Failure Assessment (qSOFA) are more suitable for screening than for prediction in the ED, and we aimed to find a light-weight, convenient prediction method through machine learning.

Methods: We accessed the MIMIC-IV for sepsis patient data in the EDs. Our dataset comprised demographic information, vital signs, and synthetic features. Extreme Gradient Boosting (XGBoost) was used to predict the risk of developing sepsis within 24 h after ED admission. Additionally, SHapley Additive exPlanations (SHAP) was employed to provide a comprehensive interpretation of the model's results. Ten percent of the patients were randomly selected as the testing set, while the remaining patients were used for training with 10-fold cross-validation.

Results: For 10-fold cross-validation on 14,957 samples, we reached an accuracy of 84.1%±0.3% and an area under the receiver operating characteristic (ROC) curve of 0.92±0.02. The model achieved similar performance on the testing set of 1,662 patients. SHAP values showed that the five most important features were acuity, arrival transportation, age, shock index, and respiratory rate.

Conclusion: Machine learning models such as XGBoost may be used for sepsis prediction using only a small amount of data conveniently collected in the ED triage stage. This may help reduce workload in the ED and warn medical workers against the risk of sepsis in advance.

In 2009, the World Health Organization included snakebite on the list of neglected tropical diseases, acknowledging it as a common occupational hazard for farmers, plantation workers, and others, causing tens of thousands of deaths and chronic physical disabilities every year. This guideline aims to provide practical information to help clinical professionals evaluate and treat snakebite victims. These recommendations are based on clinical experience and clinical research evidence. This guideline focuses on the following topics: snake venom, clinical manifestations, auxiliary examination, diagnosis, treatments, and prevention.

Background: The accelerated diagnostic protocol (ADP) using the Emergency Department Assessment of Chest pain Score (EDACS-ADP), a tool to identify patients at low risk of a major adverse cardiac event (MACE) among patients presenting with chest pain to the emergency department, was developed using a contemporary troponin assay. This study was performed to validate and compare the performance of the EDACS-ADP incorporating high-sensitivity cardiac troponin I between patients who had a 30-day MACE with and without unstable angina (MACE I and II, respectively).

Methods: A single-center prospective observational study of adult patients presenting with chest pain suggestive of acute coronary syndrome was performed. The performance of EDACS-ADP in predicting MACE was assessed by calculating the sensitivity and negative predictive value.

Results: Of the 1,304 patients prospectively enrolled, 399 (30.6%; 95% confidence interval [95% CI]: 27.7%-33.8%) were considered low-risk using the EDACS-ADP. Among them, the rates of MACE I and II were 1.3% (5/399) and 1.0% (4/399), respectively. The EDACS-ADP showed sensitivities and negative predictive values of 98.8% (95% CI: 97.2%-99.6%) and 98.7% (95% CI: 97.0%-99.5%) for MACE I and 98.7% (95% CI: 96.8%-99.7%) and 99.0% (95% CI: 97.4%-99.6%) for MACE II, respectively.

Conclusion: EDACS-ADP could help identify patients as safe for early discharge. However, when unstable angina was added to the outcome, the 30-day MACE rate among the designated low-risk patients remained above the level acceptable for early discharge without further evaluation.