Objective: RapidRhino is widely used in emergency departments (EDs) to treat epistaxis, and we have used RapidRhino plus epinephrine empirically. In this study, we evaluated the effectiveness of RapidRhino plus epinephrine compared to RapidRhino with saline. Methods: This prospective randomized study was performed on patients with epistaxis who visited our ED between October 2021 and January 2023. Patients were randomized to RapidRhino plus epinephrine or RapidRhino groups by drawing numbers. Subgroup analyses were performed on patients who received or did not receive anticoagulants or antiplatelets. Results: The overall success rates for RapidRhino with saline and RapidRhino with epinephrine were both high (92% and 94%, respectively), but the 10-minute success rates of RapidRhino with saline and RapidRhino with epinephrine were 57.4% and 78%.0%, respectively, which was a significant difference (P=0.001). In patients administered anticoagulants, initial success rate of RapidRhino with epinephrine was higher than that of RapidRhino with saline (83.3% and 62.9%, respectively, P=0.046), and these results were confirmed by adjusted logistic regression analyses-for all patients (adjusted odds ratio [aOR]=2.42; 95% confidence interval [CI], 1.28-4.58) and for patients treated with anticoagulants (aOR=6.31; 95% CI, 1.17-34.17). Conclusion RapidRhino with epinephrine may be more effective at controlling hemorrhage than RapidRhino. The combined administration of RapidRhino and epinephrine might reduce the time spent in emergency departments by epistaxis patients.

Objective: The purpose of this study was to develop a machine learning-based model (eXtreme Gradient boost [XGBoost]) that can accurately predict the severity of acute cholangitis in patients. The model was designed to simplify the classification process compared to conventional methods. Methods: We retrospectively collected data from patients with cholangitis who visited the emergency department of a secondary medical institution in Seongnam, Korea from January 1, 2015 to December 31, 2019. The patients were divided into three groups (Grade I, II, III) based on severity according to the Tokyo Guidelines 2018/2013 (TG18/13) severity assessment criteria for cholangitis. We used algorithms to select variables of high relevance associated with the grade of severity. For the XGBoost models, data were divided into a train set and a validation set by the random split method. The train set was trained in XGBoost models using only the top seven variables. The area under the receiver operating characteristic (AUROC) and the area under the precision-recall curve (AUPRC) were obtained from the validation set. Results: 796 patients were enrolled. The top 7 variables associated with the grade of severity were albumin, white blood cells, blood urea nitrogen, troponin T, platelets, creatinine, prothrombin time, and international normalized ratio. The AUROC values were 0.881 (Grade I), 0.836 (Grade II), and 0.932 (Grade III). The AUPRC values were 0.457 (Grade I), 0.820 (Grade II), and 0.880 (Grade III). Conclusion We believe that the developed XGBoost model is a useful tool for predicting the severity of acute cholangitis with high accuracy and fewer variables than the conventional severity classification method.

OBJECTIVES: We estimated the population prevalence of antibodies to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), including unreported infections, through a Korea Seroprevalence Study of Monitoring of SARS-CoV-2 Antibody Retention and Transmission (K-SEROSMART) in 258 communities throughout Korea. METHODS: In August 2022, a survey was conducted among 10,000 household members aged 5 years and older, in households selected through two stage probability random sampling. During face-to-face household interviews, participants self-reported their health status, COVID-19 diagnosis and vaccination history, and general characteristics. Subsequently, participants visited a community health center or medical clinic for blood sampling. Blood samples were analyzed for the presence of antibodies to spike proteins (anti-S) and antibodies to nucleocapsid proteins (anti-N) SARS-CoV-2 proteins using an electrochemiluminescence immunoassay. To estimate the population prevalence, the PROC SURVEYMEANS statistical procedure was employed, with weighting to reflect demographic data from July 2022. RESULTS: In total, 9,945 individuals from 5,041 households were surveyed across 258 communities, representing all basic local governments in Korea. The overall population-adjusted prevalence rates of anti-S and anti-N were 97.6% and 57.1%, respectively. Since the Korea Disease Control and Prevention Agency has reported a cumulative incidence of confirmed cases of 37.8% through July 31, 2022, the proportion of unreported infections among all COVID-19 infection was suggested to be 33.9%. CONCLUSIONS The K-SEROSMART represents the first nationwide, community-based seroepidemiologic survey of COVID-19, confirming that most individuals possess antibodies to SARS-CoV-2 and that a significant number of unreported cases existed. Furthermore, this study lays the foundation for a surveillance system to continuously monitor transmission at the community level and the response to COVID-19.