A Novel Artificial Intelligence-Enhanced Digital Network for Prehospital Emergency Support: Community Intervention Study.

Background: Efficient emergency patient transport systems, which are crucial for delivering timely medical care to individuals in critical situations, face certain challenges. To address this, CONNECT-AI (CONnected Network for EMS Comprehensive Technical-Support using Artificial Intelligence), a novel digital platform, was introduced. This artificial intelligence (AI)-based network provides comprehensive technical support for the real-time sharing of medical information at the prehospital stage.

Impact of emergency department overcrowding on the occurrence of in-hospital cardiac arrest.

We aimed to determine whether emergency department (ED) overcrowding affects the occurrence of in-hospital cardiac arrest (IHCA) requiring resuscitation in the ED. This retrospective study was conducted in the ED of a single hospital. We applied the propensity score-matching method to adjust for differences in clinical characteristics in patients who visited the ED during overcrowded conditions.

Predictability of the emergency department triage system during the COVID-19 pandemic.

Objective: Emergency department (ED) triage systems are used to classify the severity and urgency of emergency patients, and Korean medical institutions use the Korean Triage and Acuity Scale (KTAS). During the COVID-19 pandemic, appropriate treatment for emergency patients was delayed due to various circumstances, such as overcrowding of EDs, lack of medical workforce resources, and increased workload on medical staff. The purpose of this study was to evaluate the accuracy of the KTAS in predicting the urgency of emergency patients during the COVID-19 pandemic.

Characteristics of fall-from-height patients: a retrospective comparison of jumpers and fallers using a multi-institutional registry.

Objective: Fall from height (FFH) is a major public health problem that can result in severe injury, disability, and death. This study investigated how the characteristics of jumpers and fallers differ.

Methods: This was a retrospective study of FFH patients enrolled in an Emergency Department-based Injury In-depth Surveillance (EDIIS) registry between 2011 and 2018.

Nogo receptor-Fc delivered by haematopoietic cells enhances neurorepair in a multiple sclerosis model.

Nogo receptor 1 is the high affinity receptor for the potent myelin-associated inhibitory factors that make up part of the inflammatory extracellular milieu during experimental autoimmune encephalomyelitis. Signalling through the Nogo receptor 1 complex has been shown to be associated with axonal degeneration in an animal model of multiple sclerosis, and neuronal deletion of this receptor homologue, in a disease specific manner, is associated with preserving axons even in the context of neuroinflammation. The local delivery of Nogo receptor(1-310)-Fc, a therapeutic fusion protein, has been successfully applied as a treatment in animal models of spinal cord injury and glaucoma.

Prediction of inappropriate pre-hospital transfer of patients with suspected cardiovascular emergency diseases using machine learning: a retrospective observational study.

Background: This study aimed to develop a prediction model for transferring patients to an inappropriate hospital for suspected cardiovascular emergency diseases at the pre-hospital stage, using variables obtained from an integrated nationwide dataset, and to assess the performance of this model.

Methods: We integrated three nationwide datasets and developed a two-step prediction model utilizing a machine learning algorithm. Ninety-eight clinical characteristics of patients identified at the pre-hospital stage and 13 hospital components were used as input data for the model.

Development of Prediction Models for Acute Myocardial Infarction at Prehospital Stage with Machine Learning Based on a Nationwide Database.

Models for predicting acute myocardial infarction (AMI) at the prehospital stage were developed and their efficacy compared, based on variables identified from a nationwide systematic emergency medical service (EMS) registry using conventional statistical methods and machine learning algorithms. Patients in the EMS cardiovascular registry aged >15 years who were transferred from the public EMS to emergency departments in Korea from January 2016 to December 2018 were enrolled. Two datasets were constructed according to the hierarchical structure of the registry.

Development of a machine-learning algorithm to predict in-hospital cardiac arrest for emergency department patients using a nationwide database.

In this retrospective observational study, we aimed to develop a machine-learning model using data obtained at the prehospital stage to predict in-hospital cardiac arrest in the emergency department (ED) of patients transferred via emergency medical services. The dataset was constructed by attaching the prehospital information from the National Fire Agency and hospital factors to data from the National Emergency Department Information System. Machine-learning models were developed using patient variables, with and without hospital factors.

Impact of COVID-19 pandemic on emergency department patient volume and flow: Two countries, two hospitals.

Objectives: COVID-19 greatly disrupted the provision of emergency care across the globe. ED service delivery was urgently redesigned as human and material resources were mobilised, and patients with respiratory symptoms were isolated. This study aimed to compare ED patient volume and flow metrics before and during the COVID-19 pandemic.

Characteristics of frequent emergency department users in Korea: a 4-year retrospective analysis using Korea Health Panel Study data.

Objective: We aimed to investigate the characteristics of frequent emergency department (ED) users in Korea.

Methods: We analyzed the Korea Health Panel Study data of a sampled population from the 2005 Population Census of Korea data, and adults (age ≥18 years) who visited the ED at least once a year between 2014 and 2017 were included in the study. People who visited three or more times a year were classified as frequent users.

Effect of a Boarding Restriction Protocol on Emergency Department Crowding.

Purpose: Access block due to the lack of hospital beds causes crowding of emergency departments (ED). We initiated the "boarding restriction protocol" that limits the time of stay in the ED for patients awaiting hospitalization to 24 hours from arrival. The purpose of this study was to determine the effect of the boarding restriction protocol on ED crowding.

Predisposing Factors and Neurologic Outcomes of Patients with Elevated Serum Amylase and/or Lipase after Out-of-Hospital Cardiac Arrest: A Retrospective Cohort Study.

This study investigated the patient outcomes, incidence, and predisposing factors of elevated pancreatic enzyme levels after OHCA. We conducted a retrospective cohort study of patients treated with targeted temperature management (TTM) after out-of-hospital cardiac arrest (OHCA). Elevation of pancreatic enzyme levels was defined as serum amylase or lipase levels that were at least three times the upper limit of normal.

Characteristics of crashes and injuries on delivery motorcycles: A retrospective cohort study.

The food delivery market is growing rapidly. As most delivery riders use motorcycles, motorcycle crashes will increase along with the growing delivery market size. This study aimed at examining the proportions of motorcycle crashes and characteristics of injuries incurred while using motorcycles for occupational purposes.

Usefulness of complete blood count parameters to predict poor outcomes in cancer patients with febrile neutropenia presenting to the emergency department.

Introduction: Febrile neutropenia (FN) is one of the major complications with high mortality rates in cancer patients undergoing chemotherapy. The Multinational Association for Supportive Care in Cancer (MASCC) risk-index score has limited applicability for routine use in the emergency department (ED). This study aimed to develop simplified new nomograms that can predict 28-day mortality and the development of serious medical complications in patients with FN by using a combination of complete blood count (CBC) parameters with quick Sequential Organ Failure Assessment (qSOFA).

The elderly age criterion for increased in-hospital mortality in trauma patients: a retrospective cohort study.

Background: With an aging population, the number of elderly individuals exposed to traumatic injuries is increasing. The elderly age criterion for traumatic injuries has been inconsistent in the literature. This study aimed at specifying the elderly age criterion when the traumatic mortality rate increases.

Predictive Model of Good Clinical Outcomes in Patients Undergoing Coronary Angiography after Out-of-Hospital Cardiac Arrest: A Prospective, Multicenter Observational Study Conducted by the Korean Cardiac Arrest Research Consortium.

This observational study aimed to develop novel nomograms that predict the benefits of coronary angiography (CAG) after resuscitating patients with out-of-hospital cardiac arrest (OHCA) regardless of the electrocardiography findings and to perform an external validation of these models. Data were extracted from a prospective, multicenter registry of resuscitated patients with OHCA (October 2015-June 2018). New nomograms were developed based on variables associated with survival discharge and neurologic outcomes; their analysis included 723 and 709 patients, respectively.

Correlation between real-time heart rate and fatigue in chest compression providers during cardiopulmonary resuscitation: A simulation-based interventional study.

Background: The American Heart Association guidelines recommend switching chest compression providers at least every 2 min depending on their fatigue during cardiopulmonary resuscitation (CPR). Although the provider's heart rate is widely used as an objective indicator for detecting fatigue, the accuracy of this measure is debatable.

Objectives: This study was designed to determine whether real-time heart rate is a measure of fatigue in compression providers.

The effect of overcrowding in emergency departments on the admission rate according to the emergency triage level.

Overcrowding in emergency departments is a serious public health issue. Recent studies have reported that overcrowding in emergency departments affects not only the quality of emergency care but also clinical decisions about admission. However, no studies have examined the characteristics of the patient groups whose admission rate is influenced by such overcrowding.

Influence of Overcrowding in the Emergency Department on Return Visit within 72 Hours.

This study was conducted to determine whether overcrowding in the emergency department (ED) affects the occurrence of a return visit (RV) within 72 hours. The crowding indicator of index visit was the average number of total patients, patients under observation, and boarding patients during the first 1 and 4 hours from ED arrival time and the last 1 h before ED departure. Logistic regression analysis was conducted to determine whether each indicator affects the occurrence of RV and post-RV admission.

Use of smart glasses for ultrasound-guided peripheral venous access: a randomized controlled pilot study.

Objective: Smart glasses can provide sonographers with real-time ultrasound images. In the present study, we aimed to evaluate the utility of smart-glasses for ultrasound-guided peripheral venous access.

Methods: In this randomized, crossover-design, simulation study, 12 participants were recruited from the emergency department residents at a university hospital.

Emergency short-stay wards and boarding time in emergency departments: A propensity-score matching study.

Objectives: This study aimed to validate the effectiveness of an emergency short-stay ward (ESSW) and its impact on clinical outcomes.

Methods: This retrospective observational study was performed at an urban tertiary hospital. An ESSW has been operating in this hospital since September 2017 to reduce emergency department (ED) boarding time and only targets patients indicated for admission to the general ward from the ED.