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.

Viral load and the duration of viral shedding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are important determinants of the transmission of coronavirus disease 2019.In this study, we examined the effects of viral doses on the lung and spleen of K18-hACE2 transgenic mice by temporal histological and transcriptional analyses. Approximately, 1×105 plaque-forming units (PFU) of SARS-CoV-2 induced strong host responses in the lungs from 2 days post inoculation (dpi) which did not recover until the mice died, whereas responses to the virus were obvious at 5 days, recovering to the basal state by 14 dpi at 1×102 PFU. Further, flow cytometry showed that number of CD8+ T cells continuously increased in 1×102 PFU-virusinfected lungs from 2 dpi, but not in 1×105 PFU-virus-infected lungs. In spleens, responses to the virus were prominent from 2 dpi, and number of B cells was significantly decreased at 1×105PFU; however, 1×102 PFU of virus induced very weak responses from 2 dpi which recovered by 10 dpi. Although the defense responses returned to normal and the mice survived, lung histology showed evidence of fibrosis, suggesting sequelae of SARS-CoV-2 infection. Our findings indicate that specific effectors of the immune response in the lung and spleen were either increased or depleted in response to doses of SARS-CoV-2. This study demonstrated that the response of local and systemic immune effectors to a viral infection varies with viral dose, which either exacerbates the severity of the infection or accelerates its elimination.

Background: As the number of large-scale studies involving multiple organizations producing data has steadily increased, an integrated system for a common interoperable format is needed. In response to the coronavirus disease 2019 (COVID-19) pandemic, a number of global efforts are underway to develop vaccines and therapeutics. We are therefore observing an explosion in the proliferation of COVID-19 data, and interoperability is highly requested in multiple institutions participating simultaneously in COVID-19 pandemic research. Results: In this study, a laboratory information management system (LIMS) approach has been adopted to systemically manage various COVID-19 non-clinical trial data, including mortality, clinical signs, body weight, body temperature, organ weights, viral titer (viral replication and viral RNA), and multiorgan histopathology, from multiple institutions based on a web interface. The main aim of the implemented system is to integrate, standardize, and organize data collected from laboratories in multiple institutes for COVID-19 non-clinical efficacy testings. Six animal biosafety level 3 institutions proved the feasibility of our system. Substantial benefits were shown by maximizing collaborative high-quality non-clinical research. Conclusions This LIMS platform can be used for future outbreaks, leading to accelerated medical product development through the systematic management of extensive data from non-clinical animal studies.

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.

Purpose: Real-world experience with tocilizumab in combination with dexamethasone in patients with severe coronavirus disease (COVID-19) needs to be investigated. Materials and Methods: A retrospective cohort study was conducted to evaluate the effect of severity-adjusted dosing of dexamethasone in combination with tocilizumab for severe COVID-19 from August 2020 to August 2021. The primary endpoint was 30-day clinical recovery, which was defined as no oxygen requirement or referral after recovery. Results: A total of 66 patients were evaluated, including 33 patients in the dexamethasone (Dexa) group and 33 patients in the dexamethasone plus tocilizumab (DexaToci) group. The DexaToci group showed a statistically significant benefit in 30-day clinical recovery, compared to the Dexa group (p=0.024). In multivariable analyses, peak FiO2 within 3 days and tocilizumab combination were consistently significant for 30-day recovery (all p<0.05). The DexaToci group showed a significantly steeper decrease in FiO2 (-4.2±2.6) than the Dexa group (−2.7±2.6; p=0.021) by hospital day 15. The duration of oxygen requirement was significantly shorter in the DexaToci group than the Dexa group (median, 10.0 days vs. 17.0 days; p=0.006). Infectious complications and cellular and humoral immune responses against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the convalescence stage were not different between the two groups. Conclusion A combination of severity-adjusted dexamethasone and tocilizumab for the treatment of severe COVID-19 improved clinical recovery without increasing infectious complications or hindering the immune response against SARS-CoV-2.

Background: The purpose of the study was to translate and linguistically validate a Korean language version of the PROMIS (K-PROMIS) for the six profile adult domains: Fatigue, Pain Intensity, Pain Interference, Physical Function, Sleep Disturbance, and Ability to Participate in Social Roles and Activities. Methods: A total of 268 items were translated into Korean according to the Functional Assessment of Chronic Illness Therapy multilingual translation methodology. Participants first completed approximately 27 to 35 items and were then interviewed to evaluate the conceptual equivalence of the translation to the original English language source.The K-PROMIS items that met the a priori threshold of ≥ 20% of respondents with comprehension difficulties in the cognitive interview. Results: 54 of the 268 items were identified as difficult items to comprehend for at least 20% of respondents in Round 1. The most frequently identified K-PROMIS domain on difficult items to comprehend was the Physical function (24.5%). Most items with linguistic difficulties were Fatigue and Physical function. Cultural difficulties were only included the Physical function and Ability to Participate in Social Roles and Activities domains. 25 of 54 items were slightly revised, and then these revised items were tested with additional six participants in Round 2, and most participants had no problems to understand modified items. Conclusion The six profile adult domains of K-PROMIS have been linguistically validated.Further psychometric validation of the K-PROMIS items will provide additional information of meaningful outcomes for chronic disease and clinical setting.

Background: The purpose of the study was to translate and linguistically validate a Korean language version of the PROMIS (K-PROMIS) for the six profile adult domains: Fatigue, Pain Intensity, Pain Interference, Physical Function, Sleep Disturbance, and Ability to Participate in Social Roles and Activities. Methods: A total of 268 items were translated into Korean according to the Functional Assessment of Chronic Illness Therapy multilingual translation methodology. Participants first completed approximately 27 to 35 items and were then interviewed to evaluate the conceptual equivalence of the translation to the original English language source.The K-PROMIS items that met the a priori threshold of ≥ 20% of respondents with comprehension difficulties in the cognitive interview. Results: 54 of the 268 items were identified as difficult items to comprehend for at least 20% of respondents in Round 1. The most frequently identified K-PROMIS domain on difficult items to comprehend was the Physical function (24.5%). Most items with linguistic difficulties were Fatigue and Physical function. Cultural difficulties were only included the Physical function and Ability to Participate in Social Roles and Activities domains. 25 of 54 items were slightly revised, and then these revised items were tested with additional six participants in Round 2, and most participants had no problems to understand modified items. Conclusion The six profile adult domains of K-PROMIS have been linguistically validated.Further psychometric validation of the K-PROMIS items will provide additional information of meaningful outcomes for chronic disease and clinical setting.