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BackgroundCardiovascular disease is the leading cause of death worldwide. Early recognition, diagnosis, and reperfusion are the key elements of treatment for ST-segment elevation myocardial infarction. The absence of a prehospital 12-lead electrocardiogram (P12ECG) can cause definitive treatment delay and repeated transfer. Although guidelines highly recommend the measurement and transmission of P12ECG data, P12ECG use has not been widely established. ObjectiveThe aim of this study was to verify the time-efficiency and feasibility of the use of a patchy-type 12-lead ECG measuring and transmitting device (P-ECG) by an emergency medical technician (EMT) in an ambulance during patient transport. MethodsThis was a simulation-based prospective randomized crossover-controlled study that included EMTs. The participants were randomly assigned to one of two groups. Group A began the experiment with a conventional 12-lead ECG (C-ECG) device and then switched to the intervention device (P-ECG), whereas group B began the experiment with the P-ECG and then switched to the C-ECG. All simulations were performed inside an ambulance driving at 30 km/h. The time interval was measured from the beginning of ECG application to completion of sending the results. After the simulation, participants were administered the System Usability Scale questionnaire about usability of the P-ECG. ResultsA total of 18 EMTs were recruited for this study with a median age of 35 years. The overall interval time for the C-ECG was 254 seconds (IQR 247-270), whereas the overall interval time for the P-ECG was 130 seconds (IQR 112-150), with a significant difference (P

BackgroundThe task of monitoring and managing the entire emergency department (ED) is becoming more important due to increasing pressure on the ED. Recently, dashboards have received the spotlight as health information technology to support these tasks. ObjectiveThis study aimed to describe the development of a real-time autonomous dashboard for the ED and to evaluate perspectives of clinical staff on its usability. MethodsWe developed a dashboard based on three principles—“anytime, anywhere, at a glance;” “minimal interruption to workflow;” and “protect patient privacy”—and 3 design features—“geographical layout,” “patient-level alert,” and “real-time summary data.” Items to evaluate the dashboard were selected based on the throughput factor of the conceptual model of ED crowding. Moreover, ED physicians and nurses were surveyed using the system usability scale (SUS) and situation awareness index as well as a questionnaire we created on the basis of the construct of the Situation Awareness Rating Technique. ResultsThe first version of the ED dashboard was successfully launched in 2013, and it has undergone 3 major revisions since then because of geographical changes in ED and modifications to improve usability. A total of 52 ED staff members participated in the survey. The average SUS score of the dashboard was 67.6 points, which indicates “OK-to-Good” usability. The participants also reported that the dashboard provided efficient “concentration support” (4.15 points), “complexity representation” (4.02 points), “variability representation” (3.96 points), “information quality” (3.94 points), and “familiarity” (3.94 points). However, the “division of attention” was rated at 2.25 points. ConclusionsWe developed a real-time autonomous ED dashboard and successfully used it for 5 years with good evaluation from users.

Introduction: In this study we aimed to investigate the prognostic accuracy for predicting in-hospital mortality using respiratory Sequential Organ Failure Assessment (SOFA) scores by the conventional method of missing-value imputation with normal partial pressure of oxygen (PaO2)- and oxygen saturation (SpO2)-based estimation methods.Methods: This was a single-center, retrospective cohort study of patients with suspected infection in the emergency department. The primary outcome was in-hospital mortality. We compared the area under the receiver operating characteristics curve (AUROC) and calibration results of the conventional method (normal value imputation for missing PaO2) and six SpO2-based methods: using methods A, B, PaO2 is estimated by dividing SpO2 by a scale; with methods C and D, PaO2 was estimated by a mathematical model from a previous study; with methods E, F, respiratory SOFA scores was estimated by SpO2 thresholds and respiratory support use; with methods A, C, E are SpO2-based estimation for all PaO2 values, while methods B, D, F use such estimation only for missing PaO2 values.Results: Among the 15,119 patients included in the study, the in-hospital mortality rate was 4.9%. The missing PaO2was 56.0%. The calibration plots were similar among all methods. Each method yielded AUROCs that ranged from 0.735–0.772. The AUROC for the conventional method was 0.755 (95%confidence interval [CI] 0.736–0.773). The AUROC for method C (0.772; 95% CI 0.754–0.790) was higher than that of the conventional method, which was an SpO2-based estimation for all PaO2 values. The AUROC for total SOFA score from method E (0.815; 95% CI 0.800–0.831) was higher than that from the conventional method (0.806; 95% CI 0.790–0.822), in which respiratory SOFA was calculated by the predefined SpO2 cut-offs and oxygen support.Conclusion: In non-ICU settings, respiratory SOFA scores estimated by SpO2 might have acceptable prognostic accuracy for predicting in-hospital mortality. Our results suggest that SpO2-based respiratory SOFA score calculation might be an alternative for evaluating respiratory organ failure in the ED and clinical research settings.

Genetic, environment, and behaviour factors have a role in causing sudden cardiac arrest (SCA). We aimed to determine the strength of the association between various risk factors and SCA incidence. We conducted a multicentre case-control study at 17 hospitals in Korea from September 2017 to December 2020. The cases included out-of-hospital cardiac arrest aged 19–79 years with presumed cardiac aetiology. Community-based controls were recruited at a 1:1 ratio after matching for age, sex, and urban residence level. Multivariable conditional logistic regression analysis was conducted. Among the 1016 cases and 1731 controls, 948 cases and 948 controls were analysed. A parental history of SCA, low educational level, own heart disease, current smoking, and non-regular exercise were associated with SCA incidence (Adjusted odds ratio [95% confidence interval]: 2.51 [1.48–4.28] for parental history of SCA, 1.37 [1.38–2.25] for low edication level, 3.77 [2.38–5.90] for non-coronary artery heart disease, 4.47 [2.84–7.03] for coronary artery disease, 1.39 [1.08–1.79] for current smoking, and 4.06 [3.29–5.02] for non-regular exercise). Various risk factors related to genetics, environment, and behaviour were independently associated with the incidence of SCA. Establishing individualised SCA prevention strategies in addition to general prevention strategies is warranted. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate the risks of diabetes mellitus (DM) on out-of-hospital cardiac arrest (OHCA) and to investigate whether the risks of DM on OHCA varied according to the diagnostic and therapeutic characteristics of diabetes. We conducted a multicenter prospective case–control study in 17 University hospitals in Korea from September 2017 to December 2020. Cases were EMS-treated OHCA patients aged 20 to 79 with a presumed cardiac etiology. Community-based controls were recruited at a 1:2 ratio after matching for age, sex, and urbanization level of residence. A structured questionnaire and laboratory findings were collected from cases and controls. Multivariable conditional logistic regression analyses were conducted to estimate the risk of DM on OHCA by characteristics. A total of 772 OHCA cases and 1544 community-based controls were analyzed. A total of 242 (31.3%) OHCAs and 292 (18.9%) controls were previously diagnosed with DM. The proportions of type I DM (10.7% vs. 2.1%) and insulin therapy (15.3% vs. 6.5%) were higher in OHCAs with DM than in controls with DM. The duration of DM was longer in OHCAs than in controls (median 12 vs. 7 years). DM was associated with an increased risk of OHCA (aOR (95% CI), 2.13 (1.64–2.75)). Compared to the no diabetes group, the risks of OHCA increased in the diabetes patients with type I DM (5.26 (1.72–16.08)) and type II DM group (1.63 (1.18–2.27)), a long duration of DM prevalence (1.04 (1.02–1.06) per 1-year prevalence duration), and a high HbA1c level (1.38 (1.19–1.60) per 1% increase). By treatment modality, the aOR (95% CI) was lowest in the oral hypoglycemic agent (1.47 (1.08–2.01)) and highest in the insulin (6.63 (3.04–14.44)) groups. DM was associated with an increased risk of OHCA, and the risk magnitudes varied according to the diagnostic and therapeutic characteristics. [ABSTRACT FROM AUTHOR]