Background: The development of frailty at hospital discharge affects the clinical outcomes in severe coronavirus disease 2019 (COVID-19) survivors who had no frailty before hospitalization. We aimed to describe the prevalence of new frailty using the clinical frailty scale (CFS) and evaluate its associated factors in patients with severe COVID-19 without pre-existing frailty before hospitalization. Methods: We performed a secondary analysis of clinical data from a nationwide retrospective cohort collected from 22 hospitals between January 1, 2020 and August 31, 2021. The patients were at least 19 years old and survived until discharge after admission to the intensive care unit (ICU) because of severe COVID-19. Development of new frailty was defined as a CFS score ≥5 at hospital discharge. Results: Among 669 severe COVID-19 survivors without pre-existing frailty admitted to the ICU, the mean age was 65.2±12.8 years, 62.5% were male, and 50.2% received mechanical ventilation (MV). The mean CFS score at admission was 2.4±0.9, and new frailty developed in 27.8% (186/483). In multivariate analysis, older age, cardiovascular disease, CFS score of 3–4 before hospitalization, increased C-reactive protein level, longer duration of corticosteroid treatment, and use of MV and extracorporeal membrane oxygenation were identified as factors associated with new-onset frailty. Conclusion Our study suggests that new frailty is not uncommon and is associated with diverse factors in survivors of severe COVID-19 without pre-existing frailty.

Background: The development of frailty at hospital discharge affects the clinical outcomes in severe coronavirus disease 2019 (COVID-19) survivors who had no frailty before hospitalization. We aimed to describe the prevalence of new frailty using the clinical frailty scale (CFS) and evaluate its associated factors in patients with severe COVID-19 without pre-existing frailty before hospitalization. Methods: We performed a secondary analysis of clinical data from a nationwide retrospective cohort collected from 22 hospitals between January 1, 2020 and August 31, 2021. The patients were at least 19 years old and survived until discharge after admission to the intensive care unit (ICU) because of severe COVID-19. Development of new frailty was defined as a CFS score ≥5 at hospital discharge. Results: Among 669 severe COVID-19 survivors without pre-existing frailty admitted to the ICU, the mean age was 65.2±12.8 years, 62.5% were male, and 50.2% received mechanical ventilation (MV). The mean CFS score at admission was 2.4±0.9, and new frailty developed in 27.8% (186/483). In multivariate analysis, older age, cardiovascular disease, CFS score of 3–4 before hospitalization, increased C-reactive protein level, longer duration of corticosteroid treatment, and use of MV and extracorporeal membrane oxygenation were identified as factors associated with new-onset frailty. Conclusion Our study suggests that new frailty is not uncommon and is associated with diverse factors in survivors of severe COVID-19 without pre-existing frailty.

Background: The development of frailty at hospital discharge affects the clinical outcomes in severe coronavirus disease 2019 (COVID-19) survivors who had no frailty before hospitalization. We aimed to describe the prevalence of new frailty using the clinical frailty scale (CFS) and evaluate its associated factors in patients with severe COVID-19 without pre-existing frailty before hospitalization. Methods: We performed a secondary analysis of clinical data from a nationwide retrospective cohort collected from 22 hospitals between January 1, 2020 and August 31, 2021. The patients were at least 19 years old and survived until discharge after admission to the intensive care unit (ICU) because of severe COVID-19. Development of new frailty was defined as a CFS score ≥5 at hospital discharge. Results: Among 669 severe COVID-19 survivors without pre-existing frailty admitted to the ICU, the mean age was 65.2±12.8 years, 62.5% were male, and 50.2% received mechanical ventilation (MV). The mean CFS score at admission was 2.4±0.9, and new frailty developed in 27.8% (186/483). In multivariate analysis, older age, cardiovascular disease, CFS score of 3–4 before hospitalization, increased C-reactive protein level, longer duration of corticosteroid treatment, and use of MV and extracorporeal membrane oxygenation were identified as factors associated with new-onset frailty. Conclusion Our study suggests that new frailty is not uncommon and is associated with diverse factors in survivors of severe COVID-19 without pre-existing frailty.

Background: The development of frailty at hospital discharge affects the clinical outcomes in severe coronavirus disease 2019 (COVID-19) survivors who had no frailty before hospitalization. We aimed to describe the prevalence of new frailty using the clinical frailty scale (CFS) and evaluate its associated factors in patients with severe COVID-19 without pre-existing frailty before hospitalization. Methods: We performed a secondary analysis of clinical data from a nationwide retrospective cohort collected from 22 hospitals between January 1, 2020 and August 31, 2021. The patients were at least 19 years old and survived until discharge after admission to the intensive care unit (ICU) because of severe COVID-19. Development of new frailty was defined as a CFS score ≥5 at hospital discharge. Results: Among 669 severe COVID-19 survivors without pre-existing frailty admitted to the ICU, the mean age was 65.2±12.8 years, 62.5% were male, and 50.2% received mechanical ventilation (MV). The mean CFS score at admission was 2.4±0.9, and new frailty developed in 27.8% (186/483). In multivariate analysis, older age, cardiovascular disease, CFS score of 3–4 before hospitalization, increased C-reactive protein level, longer duration of corticosteroid treatment, and use of MV and extracorporeal membrane oxygenation were identified as factors associated with new-onset frailty. Conclusion Our study suggests that new frailty is not uncommon and is associated with diverse factors in survivors of severe COVID-19 without pre-existing frailty.

Background: The development of frailty at hospital discharge affects the clinical outcomes in severe coronavirus disease 2019 (COVID-19) survivors who had no frailty before hospitalization. We aimed to describe the prevalence of new frailty using the clinical frailty scale (CFS) and evaluate its associated factors in patients with severe COVID-19 without pre-existing frailty before hospitalization. Methods: We performed a secondary analysis of clinical data from a nationwide retrospective cohort collected from 22 hospitals between January 1, 2020 and August 31, 2021. The patients were at least 19 years old and survived until discharge after admission to the intensive care unit (ICU) because of severe COVID-19. Development of new frailty was defined as a CFS score ≥5 at hospital discharge. Results: Among 669 severe COVID-19 survivors without pre-existing frailty admitted to the ICU, the mean age was 65.2±12.8 years, 62.5% were male, and 50.2% received mechanical ventilation (MV). The mean CFS score at admission was 2.4±0.9, and new frailty developed in 27.8% (186/483). In multivariate analysis, older age, cardiovascular disease, CFS score of 3–4 before hospitalization, increased C-reactive protein level, longer duration of corticosteroid treatment, and use of MV and extracorporeal membrane oxygenation were identified as factors associated with new-onset frailty. Conclusion Our study suggests that new frailty is not uncommon and is associated with diverse factors in survivors of severe COVID-19 without pre-existing frailty.

On May 1, 2024, the Republic of Korea lifted the infectious disease crisis alert for mpox, almost two years after the first case was reported. The Korea Disease Control and Prevention Agency (KDCA) has led the response, which included diagnosis, epidemiological investigations, treatment, and vaccination. This article particularly reviews the vaccination strategy implemented and proposes suggestions for enhancing future response efforts. Initially, the KDCA recommended pre-exposure prophylaxis for high-risk groups, later expanding to include broader demographics as domestic cases rose. By April 2024, a total of 6,863 individuals had received their first vaccine dose, with 3,875 completing the second dose of third-generation vaccines. Strategies to improve future responses include addressing stigma, securing nationally representative safety data, and conducting vaccine cost-benefit analyses.These measures will help ensure a robust and effective response to future outbreaks.

Background: Worldwide, sepsis is the leading cause of death in hospitals. If mortality rates in patients with sepsis can be predicted early, medical resources can be allocated efficiently. We constructed machine learning (ML) models to predict the mortality of patients with sepsis in a hospital emergency department. Methods: This study prospectively collected nationwide data from an ongoing multicenter cohort of patients with sepsis identified in the emergency department. Patients were enrolled from 19 hospitals between September 2019 and December 2020. For acquired data from 3,657 survivors and 1,455 deaths, six ML models (logistic regression, support vector machine, random forest, extreme gradient boosting [XGBoost], light gradient boosting machine, and categorical boosting [CatBoost]) were constructed using fivefold cross-validation to predict mortality. Through these models, 44 clinical variables measured on the day of admission were compared with six sequential organ failure assessment (SOFA) components (PaO 2 /FIO 2 [PF], platelets (PLT), bilirubin, cardiovascular, Glasgow Coma Scale score, and creatinine).The confidence interval (CI) was obtained by performing 10,000 repeated measurements via random sampling of the test dataset. All results were explained and interpreted using Shapley’s additive explanations (SHAP). Results: Of the 5,112 participants, CatBoost exhibited the highest area under the curve (AUC) of 0.800 (95% CI, 0.756–0.840) using clinical variables. Using the SOFA components for the same patient, XGBoost exhibited the highest AUC of 0.678 (95% CI, 0.626–0.730). As interpreted by SHAP, albumin, lactate, blood urea nitrogen, and international normalization ratio were determined to significantly affect the results. Additionally, PF and PLTs in the SOFA component significantly influenced the prediction results. Conclusion Newly established ML-based models achieved good prediction of mortality in patients with sepsis. Using several clinical variables acquired at the baseline can provide more accurate results for early predictions than using SOFA components. Additionally, the impact of each variable was identified.

Background: Endothelial activation and stress index (EASIX) reflects endothelial dysfunction or damage. Because endothelial dysfunction is one of the key mechanisms, a few studies have shown the clinical usefulness of original and age-adjusted EASIX (age-EASIX) in patients with coronavirus disease 2019 (COVID-19). We aimed to evaluate the clinical utility of age-EASIX in predicting intensive care unit (ICU) mortality in critically ill patients with COVID-19 in South Korea. Methods: Secondary analysis was performed using clinical data retrospectively collected from 22 nationwide hospitals in South Korea between January 1, 2020, and August 31, 2021. Patients were at least 19 years old and admitted to the ICU for severe COVID-19, demanding at least high-flow nasal cannula oxygen therapy. EASIX [lactate dehydrogenase (U/L)×creatinine (mg/dL)/platelet count (109 cells/L)] and age-EASIX (EASIX×age) were calculated and log2-transformed. Results: The mean age of 908 critically ill patients with COVID-19 was 67.4 years with 59.7% male sex. The mean log2 age-EASIX was 7.38±1.45. Non-survivors (n=222, 24.4%) in the ICU had a significantly higher log2 age-EASIX than of survivors (8.2±1.52 vs. 7.1±1.32, p<0.001). log2 age-EASIX was significantly associated with ICU mortality (odds ratio, 1.541; 95% confidence interval, 1.322 to 1.796; p<0.001) and had a better area under the receiver operating characteristic curve than of the sequential organ failure assessment (SOFA) score in predicting ICU mortality (0.730 vs. 0.660, p=0.001). Conclusion Age-EASIX is significantly associated with ICU mortality and has better discriminatory ability than the SOFA score in predicting ICU mortality.

Objectives: The Panbio COVID-19 Ag Rapid Test Device (Panbio COVID-19 Ag, Abbott Rapid Diagnostics) is a lateral flow immunochromatographic assay targeting the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleoprotein in nasopharyngeal specimens for the diagnosis of coronavirus disease 2019 (COVID-19). This study aimed to verify the performance of the Panbio COVID-19 Ag for implementation in clinical laboratories. Methods: Sixty nasopharyngeal swab specimens (30 positive and 30 negative) dipped in transport medium, and COVID-19 was confirmed using real-time RT-PCR using Allplex SARS-CoV-2 assay (Seegene), were tested using the Panbio COVID-19 Ag. Reproducibility was evaluated using positive and negative control materials. Sensitivity and specificity were calculated based on the results of realtime RT-PCR as the standard test method. Results: Reproducibility was confirmed by the consistent results of repeated tests of the quality control materials. The overall sensitivity and specificity of Panbio COVID-19 Ag were 50.0% and 100.0%, respectively. Panbio COVID-19 Ag demonstrated high sensitivity (88.2%) in analyzing the detection limit cycle threshold (Ct) value of 26.67 provided by the manufacturer as a positive criterion, and the sensitivity was 100.0% for the positive criterion of Ct values <25, although it was less sensitive for Ct ≥ 25. Conclusion Considering the high sensitivity for positive samples with Ct values <25 and the rapid turnaround of results, Panbio COVID-19 Ag can be used in clinical laboratories to diagnose COVID-19 in limited settings.

Background: Data on the status of long-term follow-up (LTFU) care for childhood cancer survivors (CCSs) in Korea is lacking. This study was conducted to evaluate the current status of LTFU care for CCSs and relevant physicians’ perspectives. Methods: A nationwide online survey of pediatric hematologists/oncologists in the Republic of Korea was undertaken. Results: Overall, 47 of the 74 board-certified Korean pediatric hematologists/oncologists currently providing pediatric hematology/oncology care participated in the survey (response rate = 63.5%). Forty-five of the 47 respondents provided LTFU care for CCSs five years after the completion of primary cancer treatment. However, some of the 45 respondents provided LTFU care only for CCS with late complications or CCSs who requested LTFU care. Twenty of the 45 respondents oversaw LTFU care for adult CCSs, although pediatric hematologists/ oncologists experienced more difficulties managing adult CCSs. Many pediatric hematologists/oncologists did not perform the necessary screening test, although CCSs had risk factors for late complications, mostly because of insurance coverage issues and the lack of Korean LTFU guidelines. Regarding a desirable LTFU care system for CCSs in Korea, 27 of the 46 respondents (58.7%) answered that it is desirable to establish a multidisciplinary CCSs care system in which pediatric hematologists/oncologists and adult physicians cooperate. Conclusion The LTFU care system for CCS is underdeveloped in the Republic of Korea. It is urgent to establish an LTFU care system to meet the growing needs of Korean CCSs, which should include Korean CCSs care guidelines, provider education plans, the establishment of multidisciplinary care systems, and a supportive national healthcare policy.