Mechanical power (MP) has been reported to be associated with clinical outcomes. Because the original MP equation is derived from paralyzed patients under volume-controlled ventilation, its application in practice could be limited in patients receiving pressure-controlled ventilation (PCV). Recently, a simplified equation for patients under PCV was developed. We investigated the association between MP and intensive care unit (ICU) mortality. Methods: We conducted a retrospective analysis of Korean data from the Fourth International Study of Mechanical Ventilation. We extracted data of patients under PCV on day 1 and calculated MP using the following simplified equation: MPPCV = 0.098 ∙ respiratory rate ∙ tidal volume ∙ (ΔPinsp + positive end-expiratory pressure), where ΔPinsp is the change in airway pressure during inspiration. Patients were divided into survivors and non-survivors and then compared. Multivariable logistic regression was performed to determine association between MPPCV and ICU mortality. The interaction of MPPCV and use of neuromuscular blocking agent (NMBA) was also analyzed. Results: A total of 125 patients was eligible for final analysis, of whom 38 died in the ICU. MPPCV was higher in non-survivors (17.6 vs. 26.3 J/min, P<0.001). In logistic regression analysis, only MPPCV was significantly associated with ICU mortality (odds ratio, 1.090; 95% confidence interval, 1.029–1.155; P=0.003). There was no significant effect of the interaction between MPPCV and use of NMBA on ICU mortality (P=0.579). Conclusions: MPPCV is associated with ICU mortality in patients mechanically ventilated with PCV mode, regardless of NMBA use.

Mechanical power (MP) has been reported to be associated with clinical outcomes. Because the original MP equation is derived from paralyzed patients under volume-controlled ventilation, its application in practice could be limited in patients receiving pressure-controlled ventilation (PCV). Recently, a simplified equation for patients under PCV was developed. We investigated the association between MP and intensive care unit (ICU) mortality. Methods: We conducted a retrospective analysis of Korean data from the Fourth International Study of Mechanical Ventilation. We extracted data of patients under PCV on day 1 and calculated MP using the following simplified equation: MPPCV = 0.098 ∙ respiratory rate ∙ tidal volume ∙ (ΔPinsp + positive end-expiratory pressure), where ΔPinsp is the change in airway pressure during inspiration. Patients were divided into survivors and non-survivors and then compared. Multivariable logistic regression was performed to determine association between MPPCV and ICU mortality. The interaction of MPPCV and use of neuromuscular blocking agent (NMBA) was also analyzed. Results: A total of 125 patients was eligible for final analysis, of whom 38 died in the ICU. MPPCV was higher in non-survivors (17.6 vs. 26.3 J/min, P<0.001). In logistic regression analysis, only MPPCV was significantly associated with ICU mortality (odds ratio, 1.090; 95% confidence interval, 1.029–1.155; P=0.003). There was no significant effect of the interaction between MPPCV and use of NMBA on ICU mortality (P=0.579). Conclusions: MPPCV is associated with ICU mortality in patients mechanically ventilated with PCV mode, regardless of NMBA use.

Mechanical power (MP) has been reported to be associated with clinical outcomes. Because the original MP equation is derived from paralyzed patients under volume-controlled ventilation, its application in practice could be limited in patients receiving pressure-controlled ventilation (PCV). Recently, a simplified equation for patients under PCV was developed. We investigated the association between MP and intensive care unit (ICU) mortality. Methods: We conducted a retrospective analysis of Korean data from the Fourth International Study of Mechanical Ventilation. We extracted data of patients under PCV on day 1 and calculated MP using the following simplified equation: MPPCV = 0.098 ∙ respiratory rate ∙ tidal volume ∙ (ΔPinsp + positive end-expiratory pressure), where ΔPinsp is the change in airway pressure during inspiration. Patients were divided into survivors and non-survivors and then compared. Multivariable logistic regression was performed to determine association between MPPCV and ICU mortality. The interaction of MPPCV and use of neuromuscular blocking agent (NMBA) was also analyzed. Results: A total of 125 patients was eligible for final analysis, of whom 38 died in the ICU. MPPCV was higher in non-survivors (17.6 vs. 26.3 J/min, P<0.001). In logistic regression analysis, only MPPCV was significantly associated with ICU mortality (odds ratio, 1.090; 95% confidence interval, 1.029–1.155; P=0.003). There was no significant effect of the interaction between MPPCV and use of NMBA on ICU mortality (P=0.579). Conclusions: MPPCV is associated with ICU mortality in patients mechanically ventilated with PCV mode, regardless of NMBA use.

Mechanical power (MP) has been reported to be associated with clinical outcomes. Because the original MP equation is derived from paralyzed patients under volume-controlled ventilation, its application in practice could be limited in patients receiving pressure-controlled ventilation (PCV). Recently, a simplified equation for patients under PCV was developed. We investigated the association between MP and intensive care unit (ICU) mortality. Methods: We conducted a retrospective analysis of Korean data from the Fourth International Study of Mechanical Ventilation. We extracted data of patients under PCV on day 1 and calculated MP using the following simplified equation: MPPCV = 0.098 ∙ respiratory rate ∙ tidal volume ∙ (ΔPinsp + positive end-expiratory pressure), where ΔPinsp is the change in airway pressure during inspiration. Patients were divided into survivors and non-survivors and then compared. Multivariable logistic regression was performed to determine association between MPPCV and ICU mortality. The interaction of MPPCV and use of neuromuscular blocking agent (NMBA) was also analyzed. Results: A total of 125 patients was eligible for final analysis, of whom 38 died in the ICU. MPPCV was higher in non-survivors (17.6 vs. 26.3 J/min, P<0.001). In logistic regression analysis, only MPPCV was significantly associated with ICU mortality (odds ratio, 1.090; 95% confidence interval, 1.029–1.155; P=0.003). There was no significant effect of the interaction between MPPCV and use of NMBA on ICU mortality (P=0.579). Conclusions: MPPCV is associated with ICU mortality in patients mechanically ventilated with PCV mode, regardless of NMBA use.

Background: Inflammasomes are key in the initiation of inflammatory responses and serve to de-fend the organism. However, when the immune system is imbalanced, these complexes contribute to tumor progression. The purpose of this study was to investigate the effect of non-canonical inflammasomes on glioma malignancy. Methods: We performed bioinformatics analysis to confirm the expression of canonical andnon-canonical inflammasome-related molecules according to the degree of malignancy through immunohistochemical examination of glioma tissues obtained with patient consent from our institution. Results: Bioinformatics analysis confirmed that the expression levels of non-canonical inflam-masome-related molecules were significantly higher in tumor tissues than in normal tissues, and they also increased according to malignancy, which adversely affected the survival rate. Furthermore, in gliomas, positive correlations were found between N-form gasdermin-D, a key molecule associated with the non-canonical inflammasome, and other related molecules, including NLRP3, caspase-1, caspase-4, and caspase-5. These results were verified by immunohistochemical examination of glioma tissues, and the expression levels of these molecules also increased significantly with increasing grade.In addition, the features of pyroptosis were confirmed. Conclusion This study identified the potential of non-canonical inflammasomes as aggressiveness markers for gliomas and presented a perspective for improving glioma treatment.

Background/Aims: There are few studies describing contemporary status of mechanical ventilation in Korea. We investigated changes in management and outcome of mechanical ventilation in Korea. Methods: International, prospective observational cohort studies have been conducted every 6 years since 1998. Korean intensive care units (ICUs) participated in 2010 and 2016 cohorts. We compared 2016 and 2010 Korean data. Results: Two hundred and twenty-six patients from 18 ICUs and 275 patients from 12 ICUs enrolled in 2016 and 2010, respectively. In 2016 compared to 2010, use of non-invasive ventilation outside ICU increased (10.2% vs. 2.5%, p = 0.001). Pressure-control ventilation was the most common mode in both groups. Initial tidal volume (7.1 mL/kg vs. 7.4 mL/kg, p = 0.372) and positive end-expiratory pressure (6 cmH2O vs. 6 cmH2O, p = 0.141) were similar, but peak pressure (22 cmH2O vs. 24 cmH2O, p = 0.011) was lower in 2016. More patients received sedatives (70.7% vs. 57.0%, p = 0.002) and analgesics (86.5% vs. 51.1%, p < 0.001) in 2016. The awakening (48.4% vs. 31.0%, p = 0.002) was more frequently attempted in 2016. The accidental extubation rate decreased to one tenth of what it was in 2010 (1.1% vs. 10.2%, p < 0.001). The ICU mortality did not change (31.4% 35.6%, p = 0.343) but ICU length of stay showed a decreasing trend (9 days vs. 10 days, p = 0.054) in 2016. Conclusions There were temporal changes in care of patients on mechanical ventilation including better control of pain and agitation, and active attempt of awakening.

Background: Although respiratory tract infection is one of the most important factors triggering acute exacerbation of chronic obstructive pulmonary disease (AE-COPD), limited data are available to suggest an epidemiologic pattern of microbiology in South Korea. Methods: A multicenter observational study was conducted between January 2015 and December 2018 across 28 hospitals in South Korea. Adult patients with moderate-to-severe acute exacerbations of COPD were eligible to participate in the present study. The participants underwent all conventional tests to identify etiology of microbial pathogenesis. The primary outcome was the percentage of different microbiological pathogens causing AE-COPD. A comparative microbiological analysis of the patients with overlapping asthma–COPD (ACO) and pure COPD was performed. Results: We included 1,186 patients with AE-COPD. Patients with pure COPD constituted 87.9% and those with ACO accounted for 12.1%. Nearly half of the patients used an inhaled corticosteroid-containing regimen and one-fifth used systemic corticosteroids. Respiratory pathogens were found in 55.3% of all such patients. Bacteria and viruses were detected in 33% and 33.2%, respectively. Bacterial and viral coinfections were found in 10.9%. The most frequently detected bacteria were Pseudomonas aeruginosa (9.8%), and the most frequently detected virus was influenza A (10.4%). Multiple bacterial infections were more likely to appear in ACO than in pure COPD (8.3% vs. 3.6%, p=0.016). Conclusion Distinct microbiological patterns were identified in patients with moderate-to-severe AE-COPD in South Korea. These findings may improve evidence-based management of patients with AE-COPD and represent the basis for further studies investigating infectious pathogens in patients with COPD.

Objectives: This study aimed to propose an efficient mental health service plan to be implemented during epidemics by identifying the mental health characteristics of people who have returned from countries with large-scale coronavirus disease-2019 (COVID-19) outbreaks. Methods: We analyzed the mental health evaluation scale data submitted by 504 quarantined people who had returned from countries hit by the COVID-19 pandemic from January to April 2020 through a government support project. Results: The average age of the study group was 35.6±8.72 years, and males accounted for 67.1% and females 32.9% of the total subjects. The screening score for post-traumatic stress disorder was met by 12.1% of the subjects. Moderate to high level of depression and anxiety symptoms were seen in 10.7% and 7.0%, respectively. Also, 2.2% of the group complained of clinical level somatization symptoms, and 1.4% were evaluated as being at a high risk of suicide. The average scores and the proportion of subjects at high risk on all scales were significantly higher in female than in male. In a comparison by age, the average score of post-traumatic stress symptoms was significantly higher in subjects in their 20s than those in their 50s, and the proportion of the subjects at high risk for post-traumatic stress symptoms also showed a significant variation between age groups. However, there were no significant differences by age with respect to depression, anxiety, somatic symptoms, and suicidal tendencies. Conclusion During an epidemic, the mental health problems of people may increase, and the risk appears to be higher in female and young adults. Therefore, in addition to strong protection policies, a customized support system for each target group is required.

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: Aging is one of major causes triggering neurophysiological changes in many brain substructures, including the hippocampus, which has a major role in learning and memory. Thioredoxin (Trx) is a class of small redox proteins. Among the Trx family, Trx2 plays an important role in the regulation of mitochondrial membrane potential and is controlled by TrxR2. Hitherto, age-dependent alterations in Trx2 and TrxR2 in aged hippocampi have been poorly investigated. Therefore, the aim of this study was to examine changes in Trx2 and TrxR2 in mouse and rat hippocampi by age and to compare their differences between mice and rats. Results: Trx2 and TrxR2 levels using Western blots in mice were the highest at young age and gradually reduced with time, showing that no significant differences in the levels were found between the two subfields. In rats, however, their expression levels were the lowest at young age and gradually increased with time. Nevertheless, there were no differences in cellular distribution and morphology in their hippocampi when it was observed by cresyl violet staining. In addition, both Trx2 and TrxR2 immunoreactivities in the CA1-3 fields were mainly shown in pyramidal cells (principal cells), showing that their immunoreactivities were altered like changes in their protein levels. Conclusions Our current findings suggest that Trx2 and TrxR2 expressions in the brain may be different according to brain regions, age and species. Therefore, further studies are needed to examine the reasons of the differences of Trx2 and TrxR2 expressions in the hippocampus between mice and rats.