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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.

Bacteremia is a life-threatening condition that has increased in prevalence over the past two decades. Prompt recognition of bacteremia is important; however, identification of bacteremia requires 1 to 2 days. This retrospective cohort study, conducted from 10 November 2014 to November 2019, among patients with suspected infection who visited the emergency department (ED), aimed to develop and validate a simple tool for predicting bacteremia. The study population was randomly divided into derivation and development cohorts. Predictors of bacteremia based on the literature and logistic regression were assessed. A weighted value was assigned to predictors to develop a prediction model for bacteremia using the derivation cohort; discrimination was then assessed using the area under the receiver operating characteristic curve (AUC). Among the 22,519 patients enrolled, 18,015 were assigned to the derivation group and 4504 to the validation group. Sixteen candidate variables were selected, and all sixteen were used as significant predictors of bacteremia (model 1). Among the sixteen variables, the top five with higher odds ratio, including procalcitonin, neutrophil–lymphocyte ratio (NLR), lactate level, platelet count, and body temperature, were used for the simple bacteremia score (model 2). The proportion of bacteremia increased according to the simple bacteremia score in both cohorts. The AUC for model 1 was 0.805 (95% confidence interval [CI] 0.785–0.824) and model 2 was 0.791 (95% CI 0.772–0.810). The simple bacteremia prediction score using only five variables demonstrated a comparable performance with the model including sixteen variables using all laboratory results and vital signs. This simple score is useful for predicting bacteremia-assisted clinical decisions. [ABSTRACT FROM AUTHOR]

This study aimed to determine the impact of modifications in emergency department (ED) practices caused by the coronavirus disease 2019 (COVID-19) pandemic on the clinical outcomes and management of patients with septic shock. We performed a retrospective study. Patients with septic shock who presented to the ED between 1 January 2018 and 19 January 2020 were allocated to the pre-COVID-19 group, whereas those who presented between 20 January 2020 and 31 December 2020 were assigned to the post-COVID-19 group. We used propensity score matching to compare the sepsis-related interventions and clinical outcomes. The primary outcome measure was in-hospital mortality. Of the 3697 patients included, 2254 were classified as pre-COVID-19 and 1143 as post-COVID-19. A total of 1140 propensity score-matched pairings were created. Overall, the in-hospital mortality rate was 25.5%, with no statistical difference between the pre- and post-COVID-19 groups (p = 0.92). In a matched cohort, the post-COVID-19 group had delayed lactate measurement, blood culture test, and infection source control (all p < 0.05). There was no significant difference in time to antibiotics (p = 0.19) or vasopressor administration (p = 0.09) between the groups. Although sepsis-related interventions were delayed during the COVID-19 pandemic, there was no significant difference in the in-hospital mortality between the pre- and post-COVID-19 groups. [ABSTRACT FROM AUTHOR]

Background: Since its introduction, telemedicine for patients with chronic diseases has been studied in various clinical settings. However, there is limited evidence of the effectiveness and medical safety of the nationwide adoption of telemedicine., Objective: This study aimed to analyze the effects of telemedicine on chronic diseases during the COVID-19 pandemic under a temporary telemedicine policy in South Korea using national claims data., Methods: Health insurance claims data were extracted over 2 years: 1 year before (from February 24, 2019, to February 23, 2020) and 1 year after the policy was implemented (from February 24, 2020, to February 23, 2021). We included all patients who used telemedicine at least once in the first year after the policy was implemented and compared them with a control group of patients who never used telemedicine. The comparison focused on health care use; the medication possession ratio (MPR); and admission rates to general wards (GWs), emergency departments (EDs), and intensive care units (ICUs) using difference-in-differences analysis. A total of 4 chronic diseases were targeted: hypertension, diabetes mellitus (DM), chronic obstructive pulmonary disease (COPD), and common mental disorders., Results: A total of 1,773,454 patients with hypertension; 795,869 patients with DM; 37,460 patients with COPD; and 167,084 patients with common mental disorders were analyzed in this study. Patients diagnosed with hypertension or DM showed increased MPRs without an increase in GW, ED, or ICU admission rates during the policy year. Moreover, patients in the DM group who did not use telemedicine had higher rates of ED, GW, and ICU admissions, and patients in the hypertension group had higher rates of GW or ICU admissions after 1 year of policy implementation. This trend was not evident in COPD and common mental disorders., Conclusions: The temporary telemedicine policy was effective in increasing medication adherence and reducing admission rates for patients with hypertension and DM; however, the efficacy of the policy was limited for patients with COPD and common mental disorders. Future studies are required to demonstrate the long-term effects of telemedicine policies with various outcome measures reflecting disease characteristics., (©Ji Ye Kang, Weon Jung, Hyun Ji Kim, Ji Hyun An, Hee Yoon, Taerim Kim, Hansol Chang, Sung Yeon Hwang, Jong Eun Park, Gun Tak Lee, Won Chul Cha, Sejin Heo, Se Uk Lee. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 20.11.2024.)

Background: Lactate is a commonly used biomarker for sepsis, although it has limitations in certain cases, suggesting the need for novel biomarkers. We evaluated the diagnostic accuracy of plasma renin concentration and renin activity for mortality and kidney outcomes in patients with sepsis with hypoperfusion or hypotension., Methods: This was a multicenter, prospective, observational study of 117 patients with septic shock treated at three tertiary emergency departments between September 2021 and October 2022. The accuracy of renin activity, renin, and lactate concentrations in predicting 28-day mortality, acute kidney injury (AKI), and renal replacement requirement was assessed using the area under the ROC curve (AUC) analysis., Results: The AUCs of initial renin activity, renin, and lactate concentrations for predicting 28-day mortality were 0.66 (95% confidence interval [CI], 0.55-0.77), 0.63 (95% CI, 0.52-0.75), and 0.65 (95% CI, 0.53-0.77), respectively, and those at 24 hrs were 0.74 (95% CI, 0.62-0.86), 0.70 (95% CI, 0.56-0.83), and 0.67 (95% CI, 0.54-0.79). Renin concentrations and renin activity outperformed initial lactate concentrations in predicting AKI within 14 days. The AUCs of renin and lactate concentrations were 0.71 (95% CI, 0.61-0.80) and 0.57 (95% CI, 0.46-0.67), respectively ( P =0.030). The AUC of renin activity (0.70; 95% CI, 0.60-0.80) was also higher than that of lactate concentration ( P =0.044)., Conclusions: Renin concentration and renin activity show comparable performance to lactate concentration in predicting 28-day mortality in patients with septic shock but superior performance in predicting AKI.

As point-of-care ultrasound (POCUS) is increasingly being used in clinical settings, ultrasound education is expanding into student curricula. We aimed to determine the status and awareness of POCUS education in Korean medical schools using a nationwide cross-sectional survey. In October 2021, a survey questionnaire consisting of 20 questions was distributed via e-mail to professors in the emergency medicine (EM) departments of Korean medical schools. The questionnaire encompassed 19 multiple-choice questions covering demographics, current education, perceptions, and barriers, and the final question was an open-ended inquiry seeking suggestions for POCUS education. All EM departments of the 40 medical schools responded, of which only 13 (33%) reported providing POCUS education. The implementation of POCUS education primarily occurred in the third and fourth years, with less than 4 hours of dedicated training time. Five schools offered a hands-on education. Among schools offering ultrasound education, POCUS training for trauma cases is the most common. Eight schools had designated professors responsible for POCUS education and only 2 possessed educational ultrasound devices. Of the respondents, 64% expressed the belief that POCUS education for medical students is necessary, whereas 36%, including those with neutral opinions, did not anticipate its importance. The identified barriers to POCUS education included faculty shortages (83%), infrastructure limitations (76%), training time constraints (74%), and a limited awareness of POCUS (29%). POCUS education in Korean medical schools was limited to a minority of EM departments (33%). To successfully implement POCUS education in medical curricula, it is crucial to clarify learning objectives, enhance faculty recognition, and improve the infrastructure. These findings provide valuable insights for advancing ultrasound training in medical schools to ensure the provision of high-quality POCUS education for future healthcare professionals., Competing Interests: The authors have no conflicts of interest to disclose., (Copyright © 2024 the Author(s). Published by Wolters Kluwer Health, Inc.)

Bacteremia is a life-threatening condition that has increased in prevalence over the past two decades. Prompt recognition of bacteremia is important; however, identification of bacteremia requires 1 to 2 days. This retrospective cohort study, conducted from 10 November 2014 to November 2019, among patients with suspected infection who visited the emergency department (ED), aimed to develop and validate a simple tool for predicting bacteremia. The study population was randomly divided into derivation and development cohorts. Predictors of bacteremia based on the literature and logistic regression were assessed. A weighted value was assigned to predictors to develop a prediction model for bacteremia using the derivation cohort; discrimination was then assessed using the area under the receiver operating characteristic curve (AUC). Among the 22,519 patients enrolled, 18,015 were assigned to the derivation group and 4504 to the validation group. Sixteen candidate variables were selected, and all sixteen were used as significant predictors of bacteremia (model 1). Among the sixteen variables, the top five with higher odds ratio, including procalcitonin, neutrophil-lymphocyte ratio (NLR), lactate level, platelet count, and body temperature, were used for the simple bacteremia score (model 2). The proportion of bacteremia increased according to the simple bacteremia score in both cohorts. The AUC for model 1 was 0.805 (95% confidence interval [CI] 0.785-0.824) and model 2 was 0.791 (95% CI 0.772-0.810). The simple bacteremia prediction score using only five variables demonstrated a comparable performance with the model including sixteen variables using all laboratory results and vital signs. This simple score is useful for predicting bacteremia-assisted clinical decisions.

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 (PaO 2 )- and oxygen saturation (SpO 2 )-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 PaO 2 ) and six SpO 2 -based methods: using methods A, B, PaO 2 is estimated by dividing SpO 2 by a scale; with methods C and D, PaO 2 was estimated by a mathematical model from a previous study; with methods E, F, respiratory SOFA scores was estimated by SpO 2 thresholds and respiratory support use; with methods A, C, E are SpO 2 -based estimation for all PaO 2 values, while methods B, D, F use such estimation only for missing PaO 2 values., Results: Among the 15,119 patients included in the study, the in-hospital mortality rate was 4.9%. The missing PaO 2 was 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 SpO 2 -based estimation for all PaO 2 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 SpO 2 cut-offs and oxygen support., Conclusion: In non-ICU settings, respiratory SOFA scores estimated by SpO 2 might have acceptable prognostic accuracy for predicting in-hospital mortality. Our results suggest that SpO 2 -based respiratory SOFA score calculation might be an alternative for evaluating respiratory organ failure in the ED and clinical research settings., Competing Interests: Conflicts of Interest: By the WestJEM article submission agreement, all authors are required to disclose all affiliations, funding sources and financial or management relationships that could be perceived as potential sources of bias. No author has professional or financial relationships with any companies that are relevant to this study. There are no conflicts of interest or sources of funding to declare.