Cutoff of the reverse shock index multiplied by the Glasgow coma scale for predicting in-hospital mortality in adult patients with trauma: a retrospective cohort study.

BACKGROUND: Early identification of patients at risk of potential death and timely transfer to appropriate healthcare facilities are critical for reducing the number of preventable trauma deaths. This study aimed to establish a cutoff value to predict in-hospital mortality using the reverse shock index multiplied by the Glasgow Coma Scale (rSIG). METHODS: This multicenter retrospective cohort study used data from 23 emergency departments in South Korea between January 2011 and December 2020. The outcome variable was the in-hospital mortality. The relationship between rSIG and in-hospital mortality was plotted using the shape-restricted regression spline method. To set a cutoff for rSIG, we found the point on the curve where mortality started to increase and the point where the slope of the mortality curve changed the most. We also calculated the cutoff value for rSIG using Youden's index. RESULTS: A total of 318,506 adult patients with trauma were included. The shape-restricted regression spline curve showed that in-hospital mortality began to increase when the rSIG value was less than 18.86, and the slope of the graph increased the most at 12.57. The cutoff of 16.5, calculated using Youden's index, was closest to the target under-triage and over-triage rates, as suggested by the American College of Surgeons, when applied to patients with an rSIG of 20 or less. In addition, in patients with traumatic brain injury, when the rSIG value was over 25, in-hospital mortality tended to increase as the rSIG value increased. CONCLUSIONS: We propose an rSIG cutoff value of 16.5 as a predictor of in-hospital mortality in adult patients with trauma. However, in patients with traumatic brain injury, a high rSIG is also associated with in-hospital mortality. Appropriate cutoffs should be established for this group in the future.

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

Background: 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 coronavirus disease 2019 (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. Methods: This study retrospectively reviewed patients who were treated in the ED during the pandemic period from January 2020 to June 2021. Patients were divided into COVID-19 screening-negative (SN group) and COVID-19 screening-positive (SP group) groups. We compared the predictability of the KTAS for urgent patients between the two groups. Results: Of 107,480 patients, the SN and SP groups included 62,776 (58.4%) and 44,704 (41.6%) patients, respectively. The odds ratios for severity variables at each KTAS level revealed a more evident discriminatory power of KTAS for severity variables in the SN group (p-value <0.001). The predictability of KTAS for severity variables was higher in the SN group than in the SP group (area under the curve, p-value <0.001). Conclusion: During the pandemic, the KTAS had low accuracy in predicting patients in critical conditions in the ED. Therefore, in future pandemic periods, supplementation of the current ED triage system should be considered in order to accurately classify the severity of patients.

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. Depending on whether the injury was intentional, FFH patients who had fallen from a height of at least 1 m were divided into two groups: jumpers and fallers. Patient characteristics, organ damage, and death were compared between the two groups, and factors that significantly affected death were identified using multivariable logistic analysis. RESULTS: Among 39,419 patients, 1,982 (5.0%) were jumpers. Of the jumpers, 977 (49.3%) were male, while 30,643 (81.9%) of fallers were male. The jumper group had the highest number of individuals in their 20s, with the number decreasing as age increased. In contrast, the number of individuals in the faller group rose until reaching their 50s, after which it declined. More thoracoabdominal, spinal, and brain injuries were found in jumpers. The in-hospital mortality of jumpers and fallers was 832 (42.0%) and 1,268 (3.4%), respectively. Intentionality was a predictor of in-hospital mortality, along with sex, age, and fall height, with an odds ratio of 7.895 (95% confidence interval, 6.746-9.240). CONCLUSION: Jumpers and fallers have different epidemiological characteristics, and jumpers experienced a higher degree of injury and mortality than fallers. Differentiated prevention and treatment strategies are needed for jumpers and fallers to reduce mortality in FFH patients.

Severe Systemic Reactions Following Bee Sting Injuries in Korea.

PURPOSE: Most bee sting injuries are benign, although sometimes they can result in life threatening outcomes, such as anaphylaxis and death. The purpose of this study was to investigate the epidemiologic status of bee sting injuries in Korea and to identify risk factors associated with severe systemic reactions (SSRs). MATERIALS AND METHODS: Cases were extracted from a multicenter retrospective registry for patients who had visited emergency departments (EDs) for bee sting injuries. SSRs were defined as hypotension or altered mental status upon ED arrival, hospitalization, or death. Patient demographics and injury characteristics were compared between SSR and non-SSR groups. Logistic regression was performed to identify risk factors for bee sting-associated SSRs, and the characteristics of fatality cases were summarized. RESULTS: Among the 9673 patients with bee sting injuries, 537 had an SSR and 38 died. The most frequent injury sites included the hands and head/face. Logistic regression analysis revealed that the occurrence of SSRs was associated with male sex [odds ratio (95% confidence interval); 1.634 (1.133-2.357)] and age [1.030 (1.020-1.041)]. Additionally, the risk of SSRs from trunk and head/face stings was high [2.858 (1.405-5.815) and 2.123 (1.333-3.382), respectively]. Bee venom acupuncture [3.685 (1.408-9.641)] and stings in the winter [4.573 (1.420-14.723)] were factors that increased the risk of SSRs. CONCLUSION: Our findings emphasize the need for implementing safety policies and education on bee sting-related incidents to protect high-risk groups.

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. As multiple sclerosis and experimental autoimmune encephalomyelitis exhibit large numbers of inflammatory cell infiltrates within the CNS lesions, we utilized transplantable haematopoietic stem cells as a cellular delivery method of the Nogo receptor(1-310)-Fc fusion protein. We identified CNS-infiltrating macrophages as the predominant immune-positive cell type that overexpressed myc-tagged Nogo receptor(1-310)-Fc fusion protein at the peak stage of experimental autoimmune encephalomyelitis. These differentiated phagocytes were predominant during the extensive demyelination and axonal damage, which are associated with the engulfment of the protein complex of Nogo receptor(1-310)-Fc binding to myelin ligands. Importantly, mice transplanted with haematopoietic stem cells transduced with the lentiviral vector carrying Nogo receptor(1-310)-Fc and recovered from the peak of neurological decline during experimental autoimmune encephalomyelitis, exhibiting axonal regeneration and eventual remyelination in the white matter tracts. There were no immunomodulatory effects of the transplanted, genetically modified haematopoietic stem cells on immune cell lineages of recipient female mice induced with experimental autoimmune encephalomyelitis. We propose that cellular delivery of Nogo receptor(1-310)-Fc fusion protein through genetically modified haematopoietic stem cells can modulate multifocal experimental autoimmune encephalomyelitis lesions and potentiate neurological recovery.

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. The primary endpoint of the model was the prediction of transfer to an inappropriate hospital. RESULTS: A total of 94,256 transferred patients in the public pre-hospital care system matched the National Emergency Department Information System data of patients with a pre-hospital cardiovascular registry created in South Korea between July 2017 and December 2018. Of these, 1,770 (6.26%) patients failed to be transferred to a capable hospital. The area under the receiver operating characteristic curve of the final predictive model was 0.813 (0.800-0.825), and the area under the receiver precision-recall curve was 0.286 (0.265-0.308). CONCLUSIONS: Our prediction model used machine learning to show favorable performance in transferring patients with suspected cardiovascular disease to a capable hospital. For our results to lead to changes in the pre-hospital care system, a digital platform for sharing real-time information should be developed.

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. METHODS: An observational study was conducted in two large urban EDs in Brisbane, Australia and Seoul, Republic of Korea. Patient volume and flow were quantified using ED presentation numbers and service times, respectively. Daily case numbers, waiting, treatment and admission delay times were compared between 2019 and 2020/2021 using time series plots. Outcomes were further classified by triage category and age group. Trends were examined alongside a timeline of health service and government policies. RESULTS: There were reductions in daily presentations for the least urgent triage categories during the early phase of the pandemic. The caseloads for the most urgent triage categories were unaffected. The trends were similar in both EDs. A reduction in waiting and admission delay times but not treatment times coincided with reduced presentations in Brisbane. This pattern gradually reversed as presentations returned to baseline. In Seoul, admission delay times returned to pre-pandemic levels despite a persistent reduction in presentation numbers. CONCLUSIONS: Total daily presentations varied considerably according to government mandated social restrictions and testing requirements in both EDs. The reductions in waiting and admission delay times corresponded with improvements in hospital capacity.

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. A total of 184,577 patients (Dataset 1) were included in the final analysis. Among them, 72,439 patients (Dataset 2) were suspected to have AMI at prehospital stage. Between the models derived using the conventional logistic regression method, the B-type model incorporated AMI-specific variables from the A-type model and exhibited a superior discriminative ability (p = 0.02). The models that used extreme gradient boosting and a multilayer perceptron yielded a higher predictive performance than the conventional logistic regression-based models for analyses that used both datasets. Each machine learning algorithm yielded different classification lists of the 10 most important features. Therefore, prediction models that use nationwide prehospital data and are developed with appropriate structures can improve the identification of patients who require timely AMI management.

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. We validated model performance and used the SHapley Additive exPlanation model interpretation. In-hospital cardiac arrest occurred in 5431 of the 1,350,693 patients (0.4%). The extreme gradient boosting model showed the best performance with area under receiver operating curve of 0.9267 when incorporating the hospital factor. Oxygen supply, age, oxygen saturation, systolic blood pressure, the number of ED beds, ED occupancy, and pulse rate were the most influential variables, in that order. ED occupancy and in-hospital cardiac arrest occurrence were positively correlated, and the impact of ED occupancy appeared greater in small hospitals. The machine-learning predictive model using the integrated information acquired in the prehospital stage effectively predicted in-hospital cardiac arrest in the ED and can contribute to the efficient operation of emergency medical systems.

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. We compared demographic, socioeconomic, and health-related factors between nonfrequent and frequent users. We used a multivariable logistic regression analysis to determine factors related to frequent ED visits. We also compared the characteristics of ED use in both nonfrequent and frequent users. RESULTS: A total of 5,090 panels were included, comprising 6,853 visits. Frequent users were 333 (6.5% of all panels), and their ED visits were 1,364 (19.9% of all ED visits). In the multivariable regression analysis, medical aid coverage (adjusted odds ratio [aOR] of the National Health Service coverage, 0.55; 95% confidence interval [CI], 0.40-0.75), unemployment (aOR of employment, 0.72; 95% CI, 0.56-0.91), prior ward admission in a year (aOR, 2.14; 95% CI, 1.67-2.75), and frequent outpatient department use (aOR, 1.72; 95% CI, 1.35-2.20) were associated with frequent use. Moreover, frequent users visited the ED of public hospitals more often than than nonfrequent users (19.2% vs. 9.8%). Medical problems rather than injury/poisoning were the more common reasons for visiting the ED (84.5% vs. 71.2%). CONCLUSION: We found that frequent ED users were likely to be those with socioeconomic disadvantage or with high demand for medical service. Based on this study, further studies on interventions to reduce frequent ED use are required for better ED services.

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. MATERIALS AND METHODS: The primary outcome was ED occupancy rate, which was calculated as the ratio of the number of occupying patients to the total number of ED beds. Time factors, such as length of stay (LOS), treatment time, and boarding time, were investigated. RESULTS: The mean of the ED occupancy rate decreased from 1.532±0.432 prior to implementation of the protocol to 1.273±0.353 after (p<0.001). According to time series analysis, the absolute effect caused by the protocol was -0.189 (-0.277 to -0.110) (p=0.001). The proportion of patients with LOS exceeding 24 hours decreased from 7.6% to 4.0% (p<0.001). Among admitted patients, ED LOS decreased from 770.7 (421.4-1587.1) minutes to 630.2 (398.0-1156.8) minutes (p<0.001); treatment time increased from 319.6 (198.5-482.8) minutes to 344.7 (213.4-519.5) minutes (p<0.001); and boarding time decreased from 298.9 (109.5-1149.0) minutes to 204.1 (98.7-545.7) minutes (p<0.001). In pre-protocol period, boarding patients accumulated in the ED during the weekdays and resolved on Friday, but this pattern was alleviated in post-period. CONCLUSION: The boarding restriction protocol was effective in alleviating ED crowding by reducing the accumulation of boarding patients in the ED during the weekdays.

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. The factors associated with elevated pancreatic enzyme levels and their association with neurologic outcomes and mortality 28 days after OHCA were analyzed. Among the 355 patients, 166 (46.8%) patients developed elevated pancreatic enzyme levels. In the multivariable analysis (odds ratio, 95% confidence interval), initial shockable rhythm (0.62, 0.39−0.98, p = 0.04), time from collapse to return of spontaneous circulation (1.02, 1.01−1.04, p < 0.001), and history of coronary artery disease (1.7, 1.01−2.87, p = 0.046) were associated with elevated pancreatic enzyme levels. After adjusting for confounding factors, elevated pancreatic enzyme levels were associated with neurologic outcomes (5.44, 3.35−8.83, p < 0.001) and mortality (3.74, 2.39−5.86, p < 0.001). Increased pancreatic enzyme levels are common in patients treated with TTM after OHCA and are associated with unfavorable neurologic outcomes and mortality at 28 days after OHCA.

Clinical Frailty Scale as a predictor of short-term mortality: A systematic review and meta-analysis of studies on diagnostic test accuracy.

BACKGROUND: The Clinical Frailty Scale (CFS) is a representative frailty assessment tool in medicine. This systematic review and meta-analysis aimed to examine whether frailty defined based on the CFS could adequately predict short-term mortality in emergency department (ED) patients. METHODS: The PubMed, EMBASE, and Cochrane libraries were searched for eligible studies until December 23, 2021. We included studies in which frailty was measured by the CFS and short-term mortality was reported for ED patients. All studies were screened by two independent researchers. Sensitivity, specificity, positive likelihood ratio (PLR), and negative likelihood ratio (NLR) values were calculated based on the data extracted from each study. Additionally, the diagnostic odds ratio (DOR) was calculated for effect size analysis, and the area under the curve (AUC) of summary receiver operating characteristics was calculated. Outcomes were in-hospital and 1-month mortality rate for patients with the CFS scores of ≥5, ≥6, and ≥7. RESULTS: Overall, 17 studies (n = 45,022) were included. Although there was no evidence of publication bias, a high degree of heterogeneity was observed. For the CFS score of ≥5, the PLR, NLR, and DOR values for in-hospital mortality were 1.446 (95% confidence interval [CI] 1.325-1.578), 0.563 (95% CI 0.355-0.893), and 2.728 (95% CI 1.872-3.976), respectively. In addition, the pooled statistics for 1-month mortality were 1.566 (95% CI 1.241-1.976), 0.582 (95% CI 0.430-0.789), and 2.696 (95% CI 1.673-4.345), respectively. Subgroup analysis of trauma patients revealed that the CFS score of ≥5 could adequately predict in-hospital mortality (PLR 1.641, 95% CI 1.242-2.170; NLR 0.580, 95% CI 0.461-0.729; DOR 2.883, 95% CI 1.994-4.168). The AUC values represented sufficient to good diagnostic accuracy. CONCLUSIONS: Evidence that is published to date suggests that the CFS is an accurate and reliable tool for predicting short-term mortality in emergency patients.

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). METHODS: In this retrospective observational study, various models comprising qSOFA score and individual CBC parameters (red cell distribution width, delta neutrophil index, mean platelet volume (MPV)) were evaluated for association with outcomes by a multivariate logistic analysis. Subsequently, nomograms were developed for outcome prediction. The primary outcome was mortality at 28 days from ED presentation; the secondary outcome was the development of serious medical complications. RESULTS: A total of 378 patients were included. Among the CBC parameters, only MPV was significantly associated with 28-day mortality and serious medical complications in patients with FN. The nomogram developed to predict 28-day mortality and serious medical complications showed good discrimination with area under the receiver-operating characteristic curve (AUC) values of 0.729 and 0.862 (95% CI, 0.780-0.943), respectively, which were not different from those of the MASCC score (0.814, 95% CI, 0.705-0.922; p = .07 and 0.921, 95% CI, 0.863-0.979; p = .11, respectively) in the validation set. The calibration of both nomograms demonstrated good agreement in the validation set. CONCLUSION: In this study, a novel prognostic nomogram using qSOFA score and MPV to identify cancer patients with FN with high risk of 28-day mortality and serious medical complications was verified and validated. Prompt management of fatal complications of FN can be possible through early prediction of poor outcomes with these new nomograms.KEY MESSAGESAmong the evaluated CBC parameters, only mean platelet volume was associated with 28-day mortality and serious medical complications in cancer patients with febrile neutropenia.A novel and rapid prognostic nomogram was developed using quick Sequential Organ Failure Assessment score and mean platelet volume to identify cancer patients with febrile neutropenia having high risk of 28-day mortality and serious medical complications.The nomogram developed to predict 28-day mortality and serious medical complications in patients with febrile neutropenia showed good discrimination and provides rapid patient evaluation that is especially applicable in the emergency department.

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

Objectives: 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.Methods: This retrospective analysis included motorcycle crash patients aged 16 years or older, who were treated in 23 emergency rooms in Korea, between 2014 and 2018. Patients were divided into two groups: delivery riders (delivery group) and others (nondelivery group). Crash and injury characteristics were compared between the two groups. In addition, trends of patients in the delivery group were compared from 2014 to 2018.Results: This study examined 26,982 motorcycle crash patients, including 3894 (14.43%) patients in the delivery group and 23,088 (85.57%) in the nondelivery group. The number of patients in the delivery group increased drastically from 583 in 2014 to 1029 in 2018, whereas the number of patients in the nondelivery group did not considerably increase (4411 in 2014 and 4462 in 2018). The delivery group had a higher proportion of crashes caused by collisions with cars or other motorcycles (p < 0.001); however, injury severity was lower. The delivery group had a lower proportion of head and face injuries but a higher proportion of extremity injuries. Furthermore, 39.9% of all crashes in this group occurred between 17:00 and 21:00. Over time, there were neither any changes in the injury severities, nor any changes in the characteristics of the delivery group, with the exception of increases in both the proportion of motorist insurance and the proportion of wearing a helmet.Conclusions: The results indicated differences in characteristics between delivery motorcycle crashes and other motorcycle crashes. Although delivery motorcycle crash severity was low compared to other motorcycle crashes, the number of patients increased significantly. Therefore, to prevent crashes, it is necessary to improve the working environment. In addition, to prevent the extremity injuries of delivery riders, the policy of wearing extremity protective gears should be considered.

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. METHODS: This is a multicenter retrospective cohort study that was conducted utilizing the data from the Emergency Department-based Injury In-depth Surveillance Registry of the Korea Disease Control and Prevention Agency, collected between January 2014 and December 2018 from 23 emergency departments. The outcome variable was in-hospital mortality. Multivariable logistic regression analysis was used to calculate the adjusted mortality rate for each age group. By using the shape-restricted regression splines method, the relationship between age and adjusted traumatic mortality was plotted and the point where the gradient of the graph had the greatest variation was calculated. RESULTS: A total of 637,491 adult trauma patients were included. The number of in-hospital deaths was 6504 (1.0%). The age at which mortality increased the most was 65.06 years old. The adjusted odds ratio for the in-hospital mortality rate with age in the ≤ 64-year-old subgroup was 1.038 (95% confidence interval (CI) 1.032-1.044) and in the ≥ 65-year-old subgroup was 1.059 (95% CI 1.050-1.068). The adjusted odds ratio for in-hospital mortality in the ≥ 65-year-old compared to the ≤ 64-year-old subgroup was 4.585 (95% CI 4.158-5.055, p < 0.001). CONCLUSIONS: This study found that the in-hospital mortality rate rose with increasing age and that the increase was the most rapid from the age of 65 years. We propose to define the elderly age criterion for traumatic injuries as ≥ 65 years of age.

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. Patient age (p < 0.001), prehospital defibrillation by emergency medical technicians (EMTs) (p = 0.003), prehospital return of spontaneous circulation (ROSC) (p = 0.02), and time from collapse to ROSC (p < 0.001) were associated with survival discharge. Patient age (p < 0.001), prehospital defibrillation by EMTs (p < 0.001), and time from collapse to ROSC (p < 0.001) were associated with neurologic outcomes. The new nomogram had a good predictive performance, with an area under the curve (AUC) of 0.8832 (95% confidence interval (CI): 0.8358-0.9305) for survival discharge and an AUC of 0.9048 (95% CI: 0.8627-0.9469) for neurologic outcomes. Novel nomograms that predict survival discharge and good neurological outcomes after CAG in patients with OHCA were developed and validated; they can be quickly and easily applied to identify patients who will benefit from CAG.

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. STUDY DESIGN: A simulation-based prospective interventional study including 110 participants. METHODS: Participants performed chest compressions in pairs for four cycles using advanced cardiovascular life support simulation. Each participant's heart rate was measured using wearable healthcare devices, and qualitative variables regarding individual compressions were obtained from computerized devices. The primary outcome was correct depth of chest compressions. The main exposure was the change in heart rate, defined as the difference between the participant's heart rate during individual compressions and that before the simulation was initiated. RESULTS: With a constant compression duration for one cycle, the overall accuracy of compression depth significantly decreased with increasing heart rate. Female participants displayed significantly decreased accuracy of compression depth with increasing heart rate (odds ratio [OR]: 0.97; 95% confidence interval [CI]: 0.95-0.98; P < .001). Conversely, male participants displayed significantly improved accuracy with increasing heart rate (OR: 1.03; 95% CI: 1.02-1.04; P < .001). CONCLUSION: Increasing heart rate could reflect fatigue in providers performing chest compressions with a constant duration for one cycle. Thus, provider rotation should be considered according to objectively measured fatigue during CPR.

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. This retrospective cohort study was conducted in a single emergency department between January 1 and December 31, 2018. Patients over 19 years old were enrolled and divided into three groups according to the degree of overcrowding-high, low, and non-based on the total number of patients in the emergency department. An emergency triage tool (the Korean Triage and Acuity Scale) was used, which categorizes patients into five different levels. We analyzed whether the degree of change in the admission rate according to the extent of overcrowding differed for each triage group. There were 73,776 patients in this study. In the analysis of all patient groups, the admission rate increased as the degree of overcrowding rose (the adjusted odds ratio for admission was 1.281 (1.225-1.339) in the high overcrowding group versus the non-overcrowding group). The analysis of the patients in each triage level showed an increase in the admission rate associated with the overcrowding, which was greater in the patient groups with a lower triage level (adjusted odds ratios for admission in the high overcrowding group versus non-overcrowding group: Korean Triage and Acuity Scale level 3 = 1.215 [1.120-1.317], level 4 = 1.294 [1.211-1.382], and level 5 = 1.954 [1.614-2.365]).

Epidemiologic characteristics of hospitalised patients after suicidal acts from 2005 to 2016 in Korea: Analysis of the Korean National Hospital Discharge Survey.

BACKGROUND: Suicide is a major cause of death in many countries, and previous suicidal attempt is known to be the predictor of future suicide. Korea is considered one of the countries with the highest suicide rate among the Organisation for Economic Co-operation and Development (OECD) members for over a decade. We aimed to investigate the epidemiologic characteristics of hospitalised patients after suicidal acts in Korea. METHODS: Data from the Korean National Hospital Discharge In-depth Injury Survey were analysed, and patients older than 9 years admitted to nationwide hospitals after suicidal acts from 2005 to 2016 were included. Their epidemiologic characteristics were explored, and we divided them into groups according to suicidal means (injury vs. poisoning) and treatment outcome (good vs. poor). The association of each characteristic with injury as suicidal means and with poor treatment outcome were explored. RESULTS: The sample included 7609 patients (corresponding to 227,571 in national population). More patients were female than male, and most were in their 40s in both sexes. Hospitalisation rate peaked in patients older than 80 years for both sexes. Male and young patients aged 10-19 years and capital residents showed relatively higher odds of choosing injury as suicidal means. Males and patients aged 40-64 and ≥65 years showed relatively higher odds of poor treatment outcome. LIMITATIONS: Some suicide attempters were excluded from the survey such as those who did not visit a hospital after the suicide attempt. CONCLUSIONS: This epidemiologic feature of suicide attempters might serve as baseline data for preventive policies regarding suicide.