Deep-learning-based personalized prediction of absolute neutrophil count recovery and comparison with clinicians for validation.

Neutropenia and its complications are major adverse effects of cytotoxic chemotherapy. The time to recovery from neutropenia varies from patient to patient, and cannot be easily predicted even by experts. Therefore, we trained a deep learning model using data from 525 pediatric patients with solid tumors to predict the day when patients recover from severe neutropenia after high-dose chemotherapy. We validated the model with data from 99 patients and compared its performance to those of clinicians. The accuracy of the model at predicting the recovery day, with a 1-day error, was 76%; its performance was better than those of the specialist group (58.59%) and the resident group (32.33%). In addition, 80% of clinicians changed their initial predictions at least once after the model's prediction was conveyed to them. In total, 86 prediction changes (90.53%) improved the recovery day estimate.

Clinical factors predicting return emergency department visits in chemotherapy-induced febrile neutropenia patients.

BACKGROUND: Although chemotherapy-induced febrile neutropenia (FN) is the most common and life-threatening oncologic emergency, the characteristics and outcomes associated with return visits to the emergency department (ED) in these patients are uncertain. Hence, we aimed to investigate the predictive factors and clinical outcomes of chemotherapy-induced FN patients returning to the ED. METHOD: This single-center, retrospective observational study spanning 14 years included chemotherapy-induced FN patients who visited the ED and were discharged. The primary outcome was a return visit to the ED within five days. We conducted logistic regression analyses to evaluate the factors influencing ED return visit. RESULTS: This study included 1318 FN patients, 154 (12.1%) of whom revisited the ED within five days. Patients (53.3%) revisited the ED owing to persistent fever (56.5%), with no intensive care unit admission and only one mortality case who was discharged hopelessly. Multivariable analysis revealed that shock index >0.9 (odds ratio [OR]: 1.45, 95% confidence interval [CI], 1.01-2.10), thrombocytopenia (<100 × 103/uL) (OR: 1.64, 95% CI, 1.11-2.42), and lactic acid level > 2 mmol/L (OR: 1.51, 95% CI, 0.99-2.25) were associated with an increased risk of a return visit to the ED, whereas being transferred into the ED from other hospitals (OR: 0.08; 95% CI, 0.005-0.38) was associated with a decreased risk of a return visit to the ED. CONCLUSION: High shock index, lactic acid, thrombocytopenia, and ED arrival type can predict return visits to the ED in chemotherapy-induced FN patients.

Patient Anxiety and Communication Experience in the Emergency Department: A Mobile, Web-Based, Mixed-Methods Study on Patient Isolation During the COVID-19 Pandemic.

BACKGROUND: Anxiety and communication difficulties in the emergency department (ED) may increase for various reasons, including isolation due to coronavirus disease 2019 (COVID-19). However, little research on anxiety and communication in EDs exists. This study explored the isolation-related anxiety and communication experiences of ED patients during the COVID-19 pandemic. METHODS: A prospective mixed-methods study was conducted from May to August 2021 at the Samsung Medical Center ED, Seoul. There were two patient groups: isolation and control. Patients measured their anxiety using the State-Trait Anxiety Inventory (STAI X1) at two time points, and we surveyed patients at two time points about factors contributing to their anxiety and communication experiences. These were measured through a mobile web-based survey. Researchers interviewed patients after their discharge. RESULTS: ED patients were not anxious regardless of isolation, and there was no statistical significance between each group at the two time points. STAI X1 was 48.4 (standard deviation [SD], 8.0) and 47.3 (SD, 10.9) for early follow-up and 46.3 (SD, 13.0) and 46.2 (SD, 13.6) for late follow-up for the isolation and control groups, respectively. The clinical process was the greatest factor contributing to anxiety as opposed to the physical environment or communication. Communication was satisfactory in 71.4% of the isolation group and 66.7% of the control group. The most important aspects of communication were information about the clinical process and patient status. CONCLUSION: ED patients were not anxious and were generally satisfied with medical providers' communication regardless of their isolation status. However, patients need clinical process information for anxiety reduction and better communication.

Impact of the 24-hour time target policy for emergency departments in South Korea: a mixed method study in a single medical center.

BACKGROUND: In South Korea, after the spread of the Middle East Respiratory Syndrome epidemic was aggravated by long stays in crowded emergency departments (EDs), a 24-hour target policy for EDs was introduced to prevent crowding and reduce patients' length of stay (LOS). The policy requires at least 95% of all patients to be admitted, discharged or transferred from an ED within 24 hours of arrival. This study analyzes the effects of the 24-hour target policy on ED LOS and compliance rates and describes the consequences of the policy. METHODS: A mixed-methods approach was applied to a retrospective observational study of ED visits combined with a survey of medical professionals. The primary measure was ED LOS, and the secondary measure was policy compliance rate which refers to the proportion of patient visits with a LOS shorter than 24 hours. Patient flow, quality of care, patient safety, staff workload, and staff satisfaction were also investigated through surveys. Mann-Whitney U and χ2 tests were used to compare variables before and after the introduction of the policy. RESULTS: The median ED LOS increased from 3.9 hours (interquartile range [IQR] = 2.1-7.6) to 4.5 hours (IQR = 2.5-8.5) after the policy was introduced. This was likely influenced by the average monthly number of patients, which greatly increased from 4819 (SD = 340) to 5870 (SD = 462) during the same period. The proportion of patients with ED LOS greater than 24 hours remained below5% only after 6 months of policy implementation, but the number of patients whose disposition was decided at 23 hours increased by 4.84 times. Survey results suggested that patient flow and quality of care improved slightly, while the workload of medical staff worsened. CONCLUSIONS: After implementing the 24-hour target policy, the proportion of patients whose ED LOS exceeded 24 hours decreased, even though the median ED LOS increased. However, the unintended consequences of the policy were observed such as increased medical professional workload and abrupt expulsion of patients before 24 hours.

Development of an Interoperable and Easily Transferable Clinical Decision Support System Deployment Platform: System Design and Development Study.

BACKGROUND: A clinical decision support system (CDSS) is recognized as a technology that enhances clinical efficacy and safety. However, its full potential has not been realized, mainly due to clinical data standards and noninteroperable platforms. OBJECTIVE: In this paper, we introduce the common data model-based intelligent algorithm network environment (CANE) platform that supports the implementation and deployment of a CDSS. METHODS: CDSS reasoning engines, usually represented as R or Python objects, are deployed into the CANE platform and converted into C# objects. When a clinician requests CANE-based decision support in the electronic health record (EHR) system, patients' information is transformed into Health Level 7 Fast Healthcare Interoperability Resources (FHIR) format and transmitted to the CANE server inside the hospital firewall. Upon receiving the necessary data, the CANE system's modules perform the following tasks: (1) the preprocessing module converts the FHIRs into the input data required by the specific reasoning engine, (2) the reasoning engine module operates the target algorithms, (3) the integration module communicates with the other institutions' CANE systems to request and transmit a summary report to aid in decision support, and (4) creates a user interface by integrating the summary report and the results calculated by the reasoning engine. RESULTS: We developed a CANE system such that any algorithm implemented in the system can be directly called through the RESTful application programming interface when it is integrated with an EHR system. Eight algorithms were developed and deployed in the CANE system. Using a knowledge-based algorithm, physicians can screen patients who are prone to sepsis and obtain treatment guides for patients with sepsis with the CANE system. Further, using a nonknowledge-based algorithm, the CANE system supports emergency physicians' clinical decisions about optimum resource allocation by predicting a patient's acuity and prognosis during triage. CONCLUSIONS: We successfully developed a common data model-based platform that adheres to medical informatics standards and could aid artificial intelligence model deployment using R or Python.

National Surveillance of Pediatric Out-of-Hospital Cardiac Arrest in Korea: The 10-Year Trend From 2009 to 2018.

BACKGROUND: This study reports trends in pediatric out-of-hospital cardiac arrest (OHCA) and factors affecting clinical outcomes by age group. METHODS: We identified 4,561 OHCA patients younger than 18 years between January 2009 and December 2018 in the Korean OHCA Registry. The patients were divided into four groups: group 1 (1 year or younger), group 2 (1 to 5 years), group 3 (6 to 12 years), and group 4 (13 to 17 years). The primary outcome was survival to hospital discharge, and the secondary outcomes were return of spontaneous circulation (ROSC) at the emergency department (ED) and good neurological status at discharge. Multivariate logistic analyses were performed. RESULTS: The incidence rate of pediatric OHCA in group 1 increased from 45.57 to 60.89 per 100,000 person-years, while that of the overall population decreased over the 10 years. The rates of ROSC at the ED, survival to hospital discharge, and good neurologic outcome were highest in group 4 (37.9%, 9.7%, 4.9%, respectively) and lowest in group 1 (28.3%, 7.1%, 3.2%). The positive factors for survival to discharge were event location of a public/commercial building or place of recreation, type of first responder, prehospital delivery of automated external defibrillator shock, initial shockable rhythm at the ED. The factors affecting survival outcomes differed by age group. CONCLUSION: This study reports comprehensive trends in pediatric OHCA in the Republic of Korea. Our findings imply that preventive methods for the targeted population should be customized by age group.

Impact of Insurance Benefits and Education on Point-of-Care Ultrasound Use in a Single Emergency Department: An Interrupted Time Series Analysis.

Background and Objectives: Point-of-care ultrasound (POCUS) is a useful tool that helps clinicians properly treat patients in emergency department (ED). This study aimed to evaluate the impact of specific interventions on the use of POCUS in the ED. Materials and Methods: This retrospective study used an interrupted time series analysis to assess how interventions changed the use of POCUS in the emergency department of a tertiary medical institute in South Korea from October 2016 to February 2021. We chose two main interventions-expansion of benefit coverage of the National Health Insurance (NHI) for emergency ultrasound (EUS) and annual ultrasound educational workshops. The primary variable was the EUS rate, defined as the number of EUS scans per 1000 eligible patients per month. We compared the level and slope of EUS rates before and after interventions. Results: A total of 5188 scanned records were included. Before interventions, the EUS rate had increased gradually. After interventions, except for the first workshop, the EUS rate immediately increased significantly (p < 0.05). The difference in the EUS rate according to the expansion of the NHI was estimated to be the largest (p < 0.001). However, the change in slope significantly decreased after the third workshop during the coronavirus disease 2019 pandemic (p = 0.004). The EUS rate increased significantly in the presence of physicians participating in intensive POCUS training (p < 0.001). Conclusion: This study found that expansion of insurance coverage for EUS and ultrasound education led to a significant and immediate increase in the use of POCUS, suggesting that POCUS use can be increased by improving education and insurance benefits.

Online Learning versus Hands-On Learning of Basic Ocular Ultrasound Skills: A Randomized Controlled Non-Inferiority Trial.

Background and objectives: Ocular ultrasound is a core application of point-of-care ultrasound (POCUS) to assist physicians in promptly identifying various ocular diseases at the bedside; however, hands-on POCUS training is challenging during a pandemic. Materials and Methods: A randomized controlled non-inferiority trial was conducted in an academic emergency department from October 2020 to April 2021. Thirty-two participants were randomly assigned to one of two groups. Group H (hands-on learning group) participated individually in a hands-on session with a standardized patient for 30 min, whereas Group O (online learning group) learned training materials and video clips for 20 min. They scanned four eyeballs of two standardized patients sequentially following the ocular POCUS scan protocol. Repeated POCUS scans were performed 2 weeks later to assess skill maintenance. Both groups completed the pre- and post-surveys and knowledge tests. Two emergency medicine faculty members blindly evaluated the data and assigned a score of 0−25. The primary endpoint was the initial total score of scan quality evaluated using non-inferiority analysis (generalized estimating equation). The secondary endpoints were total scores for scan quality after 2 weeks, scan time, and knowledge test scores. Results: The least squares means of the total scores were 21.7 (0.35) for Group O and 21.3 (0.25) for Group H, and the lower bound of the 95% confidence interval (CI) was greater than the non-inferiority margin of minus 2 (95% CI: −0.48−1.17). The second scan scores were not significantly different from those of the first scan. The groups did not differ in scanning time or knowledge test results; however, Group H showed higher subjective satisfaction with the training method (p < 0.001). Conclusion: This study showed that basic online ocular ultrasound education was not inferior to hands-on education, suggesting that it could be a useful educational approach in the pandemic era.

Hollow adrenal gland sign on dual-phase contrast-enhanced CT in critically ill patients with sepsis.

OBJECTIVE: We aimed to describe the clinical manifestations of patients with sepsis who had the hollow adrenal gland sign (HAGS) during the acute phase of resuscitation and evaluated its value in predicting in-hospital mortality. METHODS: We performed a single-center, retrospective study of patients with sepsis who visited the emergency department (ED) from November 2015 to December 2018. The patients were categorized into the positive HAGS (pHAGS) and negative HAGS (nHAGS) groups, based on its presence in initial dual-phase contrast-enhanced abdominal computed tomography (CT). The primary outcome was in-hospital mortality. A multiple logistic regression model was developed to assess variables related to in-hospital mortality. RESULTS: In all, 156 patients were included, and 36.5% (n = 57) was assigned to the pHAGS group. Both the maximal Sequential Organ Failure Assessment score within 24 h after ED arrival (10, interquartile range [IQR] 7-13 vs. 8, IQR 6-10, p < 0.01) and APACHE II score (24, IQR 20-31 vs. 20, IQR 17-25, p < 0.01) were significantly higher in the pHAGS than in the nHAGS group; the former group received significantly more interventions including vasopressors, renal replacement therapy, mechanical ventilation, and transfusions; in-hospital mortality was significantly higher in the former than in the latter group (29.8% vs. 10.1%, p < 0.01). pHAGS was an independent predictor of in-hospital mortality (adjusted odds ratio, 2.89; 95% confidence interval, 1.08-7.78; p = 0.04). CONCLUSIONS: Patients with sepsis who showed the HAGS had more severe illness than those who did not, and had an increased need for organ-supportive interventions. Presence of the HAGS was independently associated with in-hospital mortality.

Development and Validation of Unplanned Extubation Prediction Models Using Intensive Care Unit Data: Retrospective, Comparative, Machine Learning Study.

BACKGROUND: Patient safety in the intensive care unit (ICU) is one of the most critical issues, and unplanned extubation (UE) is considered the most adverse event for patient safety. Prevention and early detection of such an event is an essential but difficult component of quality care. OBJECTIVE: This study aimed to develop and validate prediction models for UE in ICU patients using machine learning. METHODS: This study was conducted in an academic tertiary hospital in Seoul, Republic of Korea. The hospital had approximately 2000 inpatient beds and 120 ICU beds. As of January 2019, the hospital had approximately 9000 outpatients on a daily basis. The number of annual ICU admissions was approximately 10,000. We conducted a retrospective study between January 1, 2010, and December 31, 2018. A total of 6914 extubation cases were included. We developed a UE prediction model using machine learning algorithms, which included random forest (RF), logistic regression (LR), artificial neural network (ANN), and support vector machine (SVM). For evaluating the model's performance, we used the area under the receiver operating characteristic curve (AUROC). The sensitivity, specificity, positive predictive value, negative predictive value, and F1 score were also determined for each model. For performance evaluation, we also used a calibration curve, the Brier score, and the integrated calibration index (ICI) to compare different models. The potential clinical usefulness of the best model at the best threshold was assessed through a net benefit approach using a decision curve. RESULTS: Among the 6914 extubation cases, 248 underwent UE. In the UE group, there were more males than females, higher use of physical restraints, and fewer surgeries. The incidence of UE was higher during the night shift as compared to the planned extubation group. The rate of reintubation within 24 hours and hospital mortality were higher in the UE group. The UE prediction algorithm was developed, and the AUROC for RF was 0.787, for LR was 0.762, for ANN was 0.763, and for SVM was 0.740. CONCLUSIONS: We successfully developed and validated machine learning-based prediction models to predict UE in ICU patients using electronic health record data. The best AUROC was 0.787 and the sensitivity was 0.949, which was obtained using the RF algorithm. The RF model was well-calibrated, and the Brier score and ICI were 0.129 and 0.048, respectively. The proposed prediction model uses widely available variables to limit the additional workload on the clinician. Further, this evaluation suggests that the model holds potential for clinical usefulness.

Developing a Time-Adaptive Prediction Model for Out-of-Hospital Cardiac Arrest: Nationwide Cohort Study in Korea.

BACKGROUND: Out-of-hospital cardiac arrest (OHCA) is a serious public health issue, and predicting the prognosis of OHCA patients can assist clinicians in making decisions about the treatment of patients, use of hospital resources, or termination of resuscitation. OBJECTIVE: This study aimed to develop a time-adaptive conditional prediction model (TACOM) to predict clinical outcomes every minute. METHODS: We performed a retrospective observational study using data from the Korea OHCA Registry in South Korea. In this study, we excluded patients with trauma, those who experienced return of spontaneous circulation before arriving in the emergency department (ED), and those who did not receive cardiopulmonary resuscitation (CPR) in the ED. We selected patients who received CPR in the ED. To develop the time-adaptive prediction model, we organized the training data set as ongoing CPR patients by the minute. A total of 49,669 patients were divided into 39,602 subjects for training and 10,067 subjects for validation. We compared random forest, LightGBM, and artificial neural networks as the prediction model methods. Model performance was quantified using the prediction probability of the model, area under the receiver operating characteristic curve (AUROC), and area under the precision recall curve. RESULTS: Among the three algorithms, LightGBM showed the best performance. From 0 to 30 min, the AUROC of the TACOM for predicting good neurological outcomes ranged from 0.910 (95% CI 0.910-0.911) to 0.869 (95% CI 0.865-0.871), whereas that for survival to hospital discharge ranged from 0.800 (95% CI 0.797-0.800) to 0.734 (95% CI 0.736-0.740). The prediction probability of the TACOM showed similar flow with cohort data based on a comparison with the conventional model's prediction probability. CONCLUSIONS: The TACOM predicted the clinical outcome of OHCA patients per minute. This model for predicting patient outcomes by the minute can assist clinicians in making rational decisions for OHCA patients.

The Use of Point-of-care Ultrasound in Emergency Medical Centers in Korea: a National Cross-sectional Survey.

BACKGROUND: Point-of-care ultrasound (POCUS) is an essential tool in emergency medicine (EM). We aimed to investigate the current status and perception of POCUS use in emergency medical centers in Korea. METHODS: A cross-sectional, nationwide survey was conducted using a mobile survey of physicians at emergency medical centers in Korea. The first message was sent on November 27, 2020, and the second message was sent on December 3, 2020 to the non-responders. The questionnaire comprised 6 categories and 24 questionnaires on demographics, current practice, education, perception, and barriers to the use of POCUS. RESULTS: A total of 467 physicians participated in the survey (a response rate of 32% among 1,458 target physicians), of which 43% were residents and 57% were EM specialists. Most of the respondents (96%) answered that they use POCUS, of which 89% reported using it at least once a week. The most frequently used types of POCUS were focused assessment with sonography for trauma (68%) and echocardiography (66%). Musculoskeletal, male genital, and pediatric scans were rarely performed tests but ranked as of the scans physicians most wanted to learn. About 73% of the respondents received ultrasound education, and 41% received ultrasound education at their own institutions. Nevertheless, education-related barriers are still the biggest deterrent to POCUS use (60%). In addition, multivariate multinomial logistic regression analysis revealed that the greater the number of ultrasound devices and the total number of physicians in the emergency center, the more likely they were to use POCUS every day. CONCLUSION: This study found that most physicians currently working in emergency medical centers in Korea more frequently perform various types of ultrasound scans compared to those 10 years prior. To further promote the use of POCUS, it is important to have an appropriate number of ultrasound devices and physicians in the emergency center along with systematic POCUS education.

Respiratory Protection Effect of Ear-loop-type KF94 Masks according to the Wearing Method in COVID-19 Pandemic: a Randomized, Open-label Study.

BACKGROUND: Ear-loop-type Korean Filter 94 masks (KF94 masks, equivalent to the N95 and FFP2) are broadly used in health care settings in Korea for the coronavirus disease 2019 pandemic. METHODS: A prospective randomized open-label study was designed to identify differences in the fitting performance between mask wearing methods in three different types of KF94 mask with ear loops between January to March 2021. General-fitting involved wearing an ear-loop-type KF94 mask, and tight-fitting involved wearing a mask aided by a clip connecting the ear loops. Each of the 30 participants wore three types of masks according to a randomly assigned order in both methods and performed a total of six quantitative fit tests (QNFTs) according to the occupational safety and health administration protocol. RESULTS: All fit factors (FFs) measured by the QNFT were significantly higher for tight-fitting method with the clip in all KF94 masks (P < 0.001). However, the total FFs were very low, with a median (interquartile range) of 6 (3-23) and 29 (9-116) for general-fitting and tight-fitting, respectively. When wearing tightly, the horizontal 3-fold type mask with adjustable ear-loop length had the highest FF, with a median of 125, and the QNFT pass rate (FF ≥ 100) increased significantly from 4 (13%) to 18 (60%). CONCLUSION: Even with sufficient filter efficiency, ear-loop-type-KF94 masks do not provide adequate protection. However, in relatively low-risk environments, wearing a face-seal adjustable KF94 mask and tight wearing with a clip can improve respiratory protection for healthcare workers. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04794556.

Effectiveness of Smartwatch Guidance for High-Quality Infant Cardiopulmonary Resuscitation: A Simulation Study.

Background and objectives: As in adults, the survival rates and neurological outcomes after infant Cardiopulmonary resuscitation (CPR) are closely related to the quality of resuscitation. This study aimed to demonstrate that using a smartwatch as a haptic feedback device increases the quality of infant CPR performed by medical professionals. Materials and methods: We designed a prospective, randomized, case-crossover simulation study. The participants (n = 36) were randomly allocated to two groups: control first group and smartwatch first group. Each CPR session consisted of 2 min of chest compressions (CCs) using the two-finger technique (TFT), 2 min of rest, and 2 min of CCs using the two-thumb encircling hands technique (TTHT). Results: The primary outcome was the variation in the "proportion of optimal chest compression duration" and "compression rate" between the smartwatch-assisted and non-smartwatch-assisted groups. The secondary outcome was the variation in the "compression depth" between two groups. The proportion of optimal CC duration was significantly higher in the smartwatch-assisted group than in the non-smartwatch-assisted group. The absolute difference from 220 was much smaller in the smartwatch-assisted group (218.02) than in the non-smartwatch-assisted group (226.59) (p-Value = 0.018). Conclusion: This study demonstrated the haptic feedback system using a smartwatch improves the quality of infant CPR by maintaining proper speed and depth regardless of the compression method used.

N95 filtering facepiece respirators do not reliably afford respiratory protection during chest compression: A simulation study.

BACKGROUND: N95 filtering facepiece respirators (N95 respirators) may not provide adequate protection against respiratory infections during chest compression due to inappropriate fitting. METHODS: This was a single-center simulation study performed from December 1, 2016, to December 31, 2016. Each participant underwent quantitative fit test (QNFT) of N95 respirators according to the Occupational Safety and Health Administration protocol. Adequacy of respirator fit was represented by the fit factor (FF), which is calculated as the number of ambient particles divided by the number inside the respirator. We divided all participants into the group that passed the overall fit test but failed at least one individual exercise (partially passed group [PPG]) and the group that passed all exercises (all passed group [APG]). Then, the participants performed three sessions of continuous chest compressions, each with a duration of 2 min, while undergoing real-time fit testing. The primary outcome was any failure (FF < 100) of the fit test during the three bouts of chest compression. RESULTS: Forty-four participants passed the QNFT. Overall, 73% (n = 32) of the participants failed at least one of the three sessions of chest compression; the number of participants who failed was significantly higher in the PPG than in the APG (94% vs. 61%; p = 0.02). Approximately 18% (n = 8) of the participants experienced mask fit failures, such as strap slipping. CONCLUSIONS: Even if the participants passed the QNFT, the N95 respirator did not provide adequate protection against respiratory infections during chest compression.

Temporal Change in Alert Override Rate with a Minimally Interruptive Clinical Decision Support on a Next-Generation Electronic Medical Record.

Background and objectives: The aim of this study is to describe the temporal change in alert override with a minimally interruptive clinical decision support (CDS) on a Next-Generation electronic medical record (EMR) and analyze factors associated with the change. Materials and Methods: The minimally interruptive CDS used in this study was implemented in the hospital in 2016, which was a part of the new next-generation EMR, Data Analytics and Research Window for Integrated kNowledge (DARWIN), which does not generate modals, 'pop-ups' but show messages as in-line information. The prescription (medication order) and alerts data from July 2016 to December 2017 were extracted. Piece-wise regression analysis and linear regression analysis was performed to determine the temporal change and factors associated with it. Results: Overall, 2,706,395 alerts and 993 doctors were included in the study. Among doctors, 37.2% were faculty (professors), 17.2% were fellows, and 45.6% trainees (interns and residents). The overall override rate was 61.9%. There was a significant change in an increasing trend at month 12 (p < 0.001). We found doctors' positions and specialties, along with the number of alerts and medication variability, were significantly associated with the change. Conclusions: In this study, we found a significant temporal change of alert override. We also found factors associated with the change, which had statistical significance.

Effectiveness of a Real-Time Ventilation Feedback Device for Guiding Adequate Minute Ventilation: A Manikin Simulation Study.

Background and objectives: It is often challenging even for skilled rescuers to provide adequate positive pressure ventilation consistently. This study aimed to investigate the effectiveness of a newly developed real-time ventilation feedback device (RTVFD) that estimates tidal volume (TV) and ventilation interval (VI) in real time. Materials and methods: We conducted a randomised, crossover, manikin simulation study. A total of 26 medical providers were randomly assigned to the RTVFD-assisted ventilation (RAV) first group (n = 13) and the non-assisted ventilation (NV) first group (n = 13). Participants provided ventilation using adult and paediatric bag valves (BVs) for 2 min each. After a washout period, the simulation was repeated by exchanging the participants' groups. Results: The primary outcome was optimal TV in the RAV and NV groups using adult and paediatric BVs. A secondary outcome was optimal VI in the RAV and NV groups using adult and paediatric BVs. The proportions of optimal TV values were higher for the RAVs when using both adult and paediatric BVs (adult BV: 47.29% vs. 18.46%, p < 0.001; paediatric BV: 89.51% vs. 72.66%, p < 0.001) than for the NVs. The proportions of optimal VI were significantly higher in RAVs when using both adult and paediatric BVs than that in NVs (adult BV: 95.64% vs. 50.20%, p < 0.001; paediatric BV: 95.83% vs. 57.14%, p < 0.001). Additionally, we found that with paediatric BVs, the simulation had a higher OR for both optimal TV (13.26; 95% CI, 9.96-17.65; p < 0.001) and VI (1.32; 1.08-1.62, p = 0.007), regardless of RTVFD use. Conclusion: Real-time feedback using RTVFD significantly improves the TV and VI in both adult and paediatric BVs in a manikin simulation study.

Accuracy of the qSOFA Score and RED Sign in Predicting Critical Care Requirements in Patients with Suspected Infection in the Emergency Department: A Retrospective Observational Study.

Background and objectives: We aimed to compare the accuracy of positive quick sequential organ failure assessment (qSOFA) scores and the RED sign in predicting critical care requirements (CCRs) in patients with suspected infection who presented to the emergency department (ED). Materials and Methods: In this retrospective observational study, we examined adult patients with suspected infection in the ED from June 2018 to September 2018. A positive qSOFA (qSOFA+) was defined as the presence of ≥2 of the following criteria: altered mental status (AMS), systolic blood pressure (SBP) < 100 mmHg, and respiratory rate (RR) ≥ 22 breaths/min. A positive RED sign (RED sign+) was defined as the presence of at least one of the RED sign criteria: AMS, skin mottling, SBP < 90 mmHg, heart rate >130 beats/min, or RR > 30 breaths/min. A qSOFA/RED+ was defined as the presence of qSOFA+ or RED+. We applied these tools twice using the initial values upon ED arrival and all values within 2 h after ED arrival. The accuracy of qSOFA+, RED+, and qSOFA/RED+ in predicting CCR was assessed. Results: Data from 5353 patients with suspected infection were analyzed. The area under the receiver operating characteristic curve (AUC) of RED+ (0.67, 95% confidence interval [CI]: 0.65-0.70) and that of qSOFA/RED+ (0.68, 95% CI: 0.66-0.70, p < 0.01) were higher than the AUC of qSOFA+ (0.59, 95% CI: 0.57-0.60) in predicting CCR on ED arrival. The qSOFA/RED+ within 2 h showed the highest accuracy (AUC 0.72, 95% CI: 0.70-0.75, p < 0.001). Conclusions: The accuracy of the RED sign in predicting CCR in patients with suspected infection who presented at ED was better than that of qSOFA. The combined use of the RED sign and qSOFA (positive qSOFA or RED sign) showed the highest accuracy.

Availability of drug at convenient stores is not associated with an increased incidence of their poisoning.

PURPOSE: In late 2012, South Korea revised the Pharmaceutical Affairs Act to make selected medications including acetaminophen, ibuprofen, and cold medications available in nonpharmacy outlets, including the 24-hour convenient stores (CVS). The objective of this study was to identify whether the characteristics and trend of self-poisonings associated with these medications were altered after the legislative change. METHODS: A retrospective study was performed using national data from the Emergency Department (ED)-based Injury In-depth Surveillance database. The patients diagnosed with poisoning were sorted from 2011 to 2016 and included in the study. As the Act was implemented from 2013, the demographic characteristics and clinical outcomes were compared before and after January 2013. A piecewise regression analysis was performed to determine the association between the monthly use of acetaminophen, medication for cold, and nonsteroidal anti-inflammatory drugs (NSAIDs) and the incidence of total poisonings before and after the January 2013. RESULTS: Among 1 536 277 patients included in the database, 17 523 patients diagnosed with poisoning were enrolled. After the legislative change, the etiology of poisoning did not change, although the frequency of hospitalization from ED was significantly increased. The monthly trend for poisoning due to acetaminophen, cold medications, and NSAIDs showed no significant slope change between before and after the legislative change. The proportional use of acetaminophen and cold medications was significantly decreased, while that of NSAIDs was unchanged before and after the legislative change. CONCLUSIONS: The change in the Pharmaceutical Affairs Act was not associated with any change in the monthly frequency of medication-related poisoning.

Protective effects of helmets on bicycle-related injuries in elderly individuals.

OBJECTIVE: The increasing frequency of bicycle-related injuries is due to the growing elderly population and their increasing physical activity. This study aimed to compare the protective effects of helmets on bicycle-related injuries in elderly individuals compared with those in younger adults. METHODS: Data from the Korean emergency department-based Injury In-depth Surveillance database from eight emergency departments during 2011-2016 were retrospectively analysed. The subjects sustained injuries while riding bicycles. Cases with unknown clinical outcomes were excluded. Covariates included mechanism, place and time of injury. The primary outcome was traumatic brain injury (TBI) incidence, and the secondary outcomes were in-hospital mortality and severe trauma. The effects of helmets on these outcomes were analysed and differences in effects were determined using logistic regression analysis. Subsequently, the differences in the effects of helmets use between age groups were examined by using interaction analysis RESULTS: Of 7181 adults, 1253 were aged >65 years. The injury incidents showed a bimodal pattern with peaks around ages 20 and 50 years. Meanwhile, the helmet-wearing rate showed a unimodal pattern with its peak at age 35-40 years; it decreased consistently with age. By multivariate analysis, helmet-wearing was associated with a reduced TBI incidence (OR 0.76; 95% CI 0.57 to 0.99) and severe trauma (OR 0.78; 95% CI 0.65 to 0.93). The effects of helmets increased in elderly individuals (TBI (p=0.022) and severe trauma (p=0.024)). CONCLUSION: The protective effects of helmets on bicycle-related injuries are greater for elderly individuals, thus reducing TBI incidence.