Background: Over the last decade, extracorporeal membrane oxygenation (ECMO) use in critically ill children has increased and is associated with favorable outcomes. Our study aims to evaluate the current status of pediatric ECMO in Korea, with a specific focus on its volume and changes in survival rates based on diagnostic indications. Methods: This multicenter study retrospectively analyzed the indications and outcomes of pediatric ECMO over 10 years in patients at 14 hospitals in Korea from January 2012 to December 2021. Four diagnostic categories (neonatal respiratory, pediatric respiratory, postcardiotomy, and cardiac-medical) and trends were compared between periods 1 (2012–2016) and 2 (2017–2021). Results: Overall, 1065 ECMO runs were performed on 1032 patients, with the annual number of cases remaining unchanged over the 10 years. ECMO was most frequently used for post-cardiotomy (42.4%), cardiac-medical (31.8%), pediatric respiratory (17.5%), and neonatal respiratory (8.2%) cases. A 3.7% increase and 6.1% decrease in pediatric respiratory and post-cardiotomy cases, respectively, were noted between periods 1 and 2.Among the four groups, the cardiac-medical group had the highest survival rate (51.2%), followed by the pediatric respiratory (46.4%), post-cardiotomy (36.5%), and neonatal respiratory (29.4%) groups. A consistent improvement was noted in patient survival over the 10 years, with a significant increase between the two periods from 38.2% to 47.1% (P = 0.004). Improvement in survival was evident in post-cardiotomy cases (30–45%, P = 0.002).Significant associations with mortality were observed in neonates, patients requiring dialysis, and those treated with extracorporeal cardiopulmonary resuscitation (P < 0.001). In pediatric respiratory ECMO, immunocompromised patients also showed a significant correlation with mortality (P < 0.001). Conclusion Pediatric ECMO demonstrated a steady increase in overall survival in Korea;however, further efforts are needed since the outcomes remain suboptimal compared with global outcomes.

Purpose: : This study investigated coronavirus disease-19 (COVID-19) related stress, resilience, and organizational commitment, and determined the factors influencing nurses’ organizational commitment at an infectious disease hospital of COVID-19. Methods: : A cross-sectional descriptive survey was conducted with 138 nurses. Data analysis, including descriptive statistics, independent t-tests, one-way ANOVA, Pearson’s correlations, and multiple regression analysis, were performed using SPSS 26.0 program. Results: : Factors influencing organizational commitment included resilience (β=0.31, p<.001), position (β=0.31, p<.001), COVID-19 related stress (β=-0.26, p<.001), and COVID-19 nursing period (β=-0.19, p=.012). These variables explained 29.6% of the organizational commitment. Conclusion : In order to enhance the organizational commitment of nurses in infectious disease hospitals of COVID-19, active program development and intervention are required at the organizational level to improve nurses’ resilience and relieve stress related to nursing infectious disease patients.

Purpose: The purpose of this study is to find out the meaning of self-care experiences of family members of mentally ill patients and describe its essential structure. Methods: The Giorgi's phenomenological research methodology was used. Six families participated in this study. In-depth individual interviews were used to collect data from October to December in 2021. Results: Five clusters of themes were identified. They were “Selfless life”, “Life on shaky grounds”, “Attempts to escape from the suffering”, “Moving forward on self-care path”, and “Happiness blooming in being together”. Conclusion The findings suggest that mental health care professionals should provide educational programs to enable families of patients with mental illness to recognize the necessity for self-care and discover ways to take care of themselves. In addition, it is necessary to develop policies to expand patient management services at mental health welfare centers so that families of patients with mental illness can secure time for self-care.

Background: Tuberculous meningitis (TBM) is the most severe form of tuberculosis, but differentiating between the diagnosis of TBM and viral meningitis (VM) is difficult. Thus, we have developed machine-learning modules for differentiating TBM from VM.Material and Methods: For the training data, confirmed or probable TBM and confirmed VM cases were retrospectively collected from five teaching hospitals in Korea between January 2000 - July 2018. Various machine-learning algorithms were used for training. The machinelearning algorithms were tested by the leave-one-out cross-validation. Four residents and two infectious disease specialists were tested using the summarized medical information. Results: The training study comprised data from 60 patients with confirmed or probable TBM and 143 patients with confirmed VM. Older age, longer symptom duration before the visit, lower serum sodium, lower cerebrospinal fluid (CSF) glucose, higher CSF protein, and CSF adenosine deaminase were found in the TBM patients. Among the various machinelearning algorithms, the area under the curve (AUC) of the receiver operating characteristics of artificial neural network (ANN) with ImperativeImputer for matrix completion (0.85; 95% confidence interval 0.79 - 0.89) was found to be the highest. The AUC of the ANN model was statistically higher than those of all the residents (range 0.67 - 0.72, P <0.001) and an infectious disease specialist (AUC 0.76; P = 0.03). Conclusion The machine-learning techniques may play a role in differentiating between TBM and VM. Specifically, the ANN model seems to have better diagnostic performance than the non-expert clinician.

Purpose: This study was conducted to investigate the nursing needs and workload of nurses according to nursing dependency for effective placement of nursing staff in the emergency department (ED). Methods: In June 2020, 256 adult patients who visited the ED were classified as two groups, suspected COVID-19 patients and general patients. The participants’electronic medical records were analyzed using descriptive statistics, t-test, x 2 -test, and Fisher's exact test using the SPSS. Results: The patient dependence score showed a significant difference between the two groups, with an average of 13.99±1.85 for the suspected COVID-19 patient group and 10.58±2.10 for the general patient group (t=12.42, p<.001). There were statistically significant differences in communication (t=3.28, p=.001), mobility (t=3.29, p=.001), nutrition, elimination, and personal care (t=7.34, p<.001) among the six domains of nursing dependency. In the domains of environment, safety, health, and social needs, the dependency score was 3 for all suspected COVID-19 patients and 1 for all general patients. Conclusion The results of this study confirmed that infection control activities of emergency patients who need isolation affect the patients’ nursing dependency on nursing care.

Background and Objectives: Cavotricuspid isthmus (CTI) block is easily achieved, and prophylactic ablation can be performed during atrial fibrillation (AF) ablation. However, the previous study was too small and short-term to clarify the efficacy of this block. Methods: Patients who underwent catheter ablation for paroxysmal AF were enrolled, and patients who had previous or induced atrial flutter (AFL) were excluded. We randomly assigned 366 patients to pulmonary vein isolation (PVI) only and prophylactic CTI ablation (PVI vs. PVI+CTI). Results: There was no significant difference in procedure time between the two groups because most CTI blocks were performed during the waiting time after the PVI (176.8±72.6 minutes in PVI vs. 174.2±76.5 minutes in PVI+CTI, p=0.75). All patients were followed up for at least 18 months, and the median follow-up was 3.4 years. The recurrence rate of AF or AFL was not different in the 2 groups (25.7% in PVI vs. 25.7% in PVI+CTI, p=0.92). The recurrence rate of any AFL was not significantly different in the 2 groups (3.3% in PVI vs. 1.6% in PVI+CTI, p=0.31). The recurrence rate of typical AFL also was not different (0.5% in PVI vs. 0.5% in PVI+CTI, p=0.99). Conclusions In this large and long-term follow-up study, prophylactic CTI ablation had no benefit in patients with paroxysmal AF without typical AFL.

Background: Tuberculous meningitis (TBM) is the most severe form of tuberculosis, but differentiating between the diagnosis of TBM and viral meningitis (VM) is difficult. Thus, we have developed machine-learning modules for differentiating TBM from VM.Material and Methods: For the training data, confirmed or probable TBM and confirmed VM cases were retrospectively collected from five teaching hospitals in Korea between January 2000 - July 2018. Various machine-learning algorithms were used for training. The machinelearning algorithms were tested by the leave-one-out cross-validation. Four residents and two infectious disease specialists were tested using the summarized medical information. Results: The training study comprised data from 60 patients with confirmed or probable TBM and 143 patients with confirmed VM. Older age, longer symptom duration before the visit, lower serum sodium, lower cerebrospinal fluid (CSF) glucose, higher CSF protein, and CSF adenosine deaminase were found in the TBM patients. Among the various machinelearning algorithms, the area under the curve (AUC) of the receiver operating characteristics of artificial neural network (ANN) with ImperativeImputer for matrix completion (0.85; 95% confidence interval 0.79 - 0.89) was found to be the highest. The AUC of the ANN model was statistically higher than those of all the residents (range 0.67 - 0.72, P <0.001) and an infectious disease specialist (AUC 0.76; P = 0.03). Conclusion The machine-learning techniques may play a role in differentiating between TBM and VM. Specifically, the ANN model seems to have better diagnostic performance than the non-expert clinician.

Purpose: This study was conducted to investigate the nursing needs and workload of nurses according to nursing dependency for effective placement of nursing staff in the emergency department (ED). Methods: In June 2020, 256 adult patients who visited the ED were classified as two groups, suspected COVID-19 patients and general patients. The participants’electronic medical records were analyzed using descriptive statistics, t-test, x 2 -test, and Fisher's exact test using the SPSS. Results: The patient dependence score showed a significant difference between the two groups, with an average of 13.99±1.85 for the suspected COVID-19 patient group and 10.58±2.10 for the general patient group (t=12.42, p<.001). There were statistically significant differences in communication (t=3.28, p=.001), mobility (t=3.29, p=.001), nutrition, elimination, and personal care (t=7.34, p<.001) among the six domains of nursing dependency. In the domains of environment, safety, health, and social needs, the dependency score was 3 for all suspected COVID-19 patients and 1 for all general patients. Conclusion The results of this study confirmed that infection control activities of emergency patients who need isolation affect the patients’ nursing dependency on nursing care.

Background and Objectives: Cavotricuspid isthmus (CTI) block is easily achieved, and prophylactic ablation can be performed during atrial fibrillation (AF) ablation. However, the previous study was too small and short-term to clarify the efficacy of this block. Methods: Patients who underwent catheter ablation for paroxysmal AF were enrolled, and patients who had previous or induced atrial flutter (AFL) were excluded. We randomly assigned 366 patients to pulmonary vein isolation (PVI) only and prophylactic CTI ablation (PVI vs. PVI+CTI). Results: There was no significant difference in procedure time between the two groups because most CTI blocks were performed during the waiting time after the PVI (176.8±72.6 minutes in PVI vs. 174.2±76.5 minutes in PVI+CTI, p=0.75). All patients were followed up for at least 18 months, and the median follow-up was 3.4 years. The recurrence rate of AF or AFL was not different in the 2 groups (25.7% in PVI vs. 25.7% in PVI+CTI, p=0.92). The recurrence rate of any AFL was not significantly different in the 2 groups (3.3% in PVI vs. 1.6% in PVI+CTI, p=0.31). The recurrence rate of typical AFL also was not different (0.5% in PVI vs. 0.5% in PVI+CTI, p=0.99). Conclusions In this large and long-term follow-up study, prophylactic CTI ablation had no benefit in patients with paroxysmal AF without typical AFL.