Objective: : Patients with traumatic brain injury (TBI) commonly exhibit a poor mental health status and can easily develop aspiration pneumonia. Thus, early proper nutrition through oral or tube feeding is difficult to achieve, leading to malnutrition. However, evidence regarding early nutritional support in the intensive care unit (ICU) is lacking. We aimed to assess the effect of early nutrition in patients with TBI admitted to the ICU. Methods: : Data of adult patients with TBI admitted to the trauma ICU of a regional trauma center in Korea between 2022 and 2023 were retrospectively analyzed. Those with ICU stay <7 days, younger than 18 years, and with underlying diseases that could alter baseline metabolism, were excluded. Nutritional support on day 4 of ICU admission was measured. The patients were classified into mortality and survival groups, and risk factors for mortality were evaluated. Subgroup analyses were performed based on TBI severity. Results: : Overall, 864 patients were diagnosed with acute TBI, of whom 227 were included in this study. The mortality rate in the study population was 15% (n=34). Those in the survival group were younger, had longer hospital stays, had a higher initial Glasglow coma scale (GCS) score, and had a higher intake of calorie supplements than those in the mortality group. In a subgroup analysis of patients with non-severe TBI (GCS >8), total calorie intake (751.4 vs. 434.2 kcal, p=0.029), total protein intake (37.5 vs. 22.1 g, p=0.045), and ratio of supplied to target calories (0.49 vs. 0.30, p=0.047) were higher in the survival group than in the mortality group. Logistic regression analysis revealed that calorie intake (B=-0.002, p=0.040) and initial hemoglobin level (B=-0.394, p=0.005) were risk factors for mortality in patients with non-severe TBI. Conclusion : More calories were supplied to the survival group than the mortality group among patients with TBI. Additionally, logistic regression analysis showed that increased calorie supply was associated with reduced mortality in patients with non-severe TBI. The mortality group had low protein intake; however, this did not emerge as a risk factor for mortality. Early sufficient nutritional support improves the prognosis of patients with TBI.

Objective: : Patients with traumatic brain injury (TBI) commonly exhibit a poor mental health status and can easily develop aspiration pneumonia. Thus, early proper nutrition through oral or tube feeding is difficult to achieve, leading to malnutrition. However, evidence regarding early nutritional support in the intensive care unit (ICU) is lacking. We aimed to assess the effect of early nutrition in patients with TBI admitted to the ICU. Methods: : Data of adult patients with TBI admitted to the trauma ICU of a regional trauma center in Korea between 2022 and 2023 were retrospectively analyzed. Those with ICU stay <7 days, younger than 18 years, and with underlying diseases that could alter baseline metabolism, were excluded. Nutritional support on day 4 of ICU admission was measured. The patients were classified into mortality and survival groups, and risk factors for mortality were evaluated. Subgroup analyses were performed based on TBI severity. Results: : Overall, 864 patients were diagnosed with acute TBI, of whom 227 were included in this study. The mortality rate in the study population was 15% (n=34). Those in the survival group were younger, had longer hospital stays, had a higher initial Glasglow coma scale (GCS) score, and had a higher intake of calorie supplements than those in the mortality group. In a subgroup analysis of patients with non-severe TBI (GCS >8), total calorie intake (751.4 vs. 434.2 kcal, p=0.029), total protein intake (37.5 vs. 22.1 g, p=0.045), and ratio of supplied to target calories (0.49 vs. 0.30, p=0.047) were higher in the survival group than in the mortality group. Logistic regression analysis revealed that calorie intake (B=-0.002, p=0.040) and initial hemoglobin level (B=-0.394, p=0.005) were risk factors for mortality in patients with non-severe TBI. Conclusion : More calories were supplied to the survival group than the mortality group among patients with TBI. Additionally, logistic regression analysis showed that increased calorie supply was associated with reduced mortality in patients with non-severe TBI. The mortality group had low protein intake; however, this did not emerge as a risk factor for mortality. Early sufficient nutritional support improves the prognosis of patients with TBI.

Objective: : Patients with traumatic brain injury (TBI) commonly exhibit a poor mental health status and can easily develop aspiration pneumonia. Thus, early proper nutrition through oral or tube feeding is difficult to achieve, leading to malnutrition. However, evidence regarding early nutritional support in the intensive care unit (ICU) is lacking. We aimed to assess the effect of early nutrition in patients with TBI admitted to the ICU. Methods: : Data of adult patients with TBI admitted to the trauma ICU of a regional trauma center in Korea between 2022 and 2023 were retrospectively analyzed. Those with ICU stay <7 days, younger than 18 years, and with underlying diseases that could alter baseline metabolism, were excluded. Nutritional support on day 4 of ICU admission was measured. The patients were classified into mortality and survival groups, and risk factors for mortality were evaluated. Subgroup analyses were performed based on TBI severity. Results: : Overall, 864 patients were diagnosed with acute TBI, of whom 227 were included in this study. The mortality rate in the study population was 15% (n=34). Those in the survival group were younger, had longer hospital stays, had a higher initial Glasglow coma scale (GCS) score, and had a higher intake of calorie supplements than those in the mortality group. In a subgroup analysis of patients with non-severe TBI (GCS >8), total calorie intake (751.4 vs. 434.2 kcal, p=0.029), total protein intake (37.5 vs. 22.1 g, p=0.045), and ratio of supplied to target calories (0.49 vs. 0.30, p=0.047) were higher in the survival group than in the mortality group. Logistic regression analysis revealed that calorie intake (B=-0.002, p=0.040) and initial hemoglobin level (B=-0.394, p=0.005) were risk factors for mortality in patients with non-severe TBI. Conclusion : More calories were supplied to the survival group than the mortality group among patients with TBI. Additionally, logistic regression analysis showed that increased calorie supply was associated with reduced mortality in patients with non-severe TBI. The mortality group had low protein intake; however, this did not emerge as a risk factor for mortality. Early sufficient nutritional support improves the prognosis of patients with TBI.

Objective: : Patients with traumatic brain injury (TBI) commonly exhibit a poor mental health status and can easily develop aspiration pneumonia. Thus, early proper nutrition through oral or tube feeding is difficult to achieve, leading to malnutrition. However, evidence regarding early nutritional support in the intensive care unit (ICU) is lacking. We aimed to assess the effect of early nutrition in patients with TBI admitted to the ICU. Methods: : Data of adult patients with TBI admitted to the trauma ICU of a regional trauma center in Korea between 2022 and 2023 were retrospectively analyzed. Those with ICU stay <7 days, younger than 18 years, and with underlying diseases that could alter baseline metabolism, were excluded. Nutritional support on day 4 of ICU admission was measured. The patients were classified into mortality and survival groups, and risk factors for mortality were evaluated. Subgroup analyses were performed based on TBI severity. Results: : Overall, 864 patients were diagnosed with acute TBI, of whom 227 were included in this study. The mortality rate in the study population was 15% (n=34). Those in the survival group were younger, had longer hospital stays, had a higher initial Glasglow coma scale (GCS) score, and had a higher intake of calorie supplements than those in the mortality group. In a subgroup analysis of patients with non-severe TBI (GCS >8), total calorie intake (751.4 vs. 434.2 kcal, p=0.029), total protein intake (37.5 vs. 22.1 g, p=0.045), and ratio of supplied to target calories (0.49 vs. 0.30, p=0.047) were higher in the survival group than in the mortality group. Logistic regression analysis revealed that calorie intake (B=-0.002, p=0.040) and initial hemoglobin level (B=-0.394, p=0.005) were risk factors for mortality in patients with non-severe TBI. Conclusion : More calories were supplied to the survival group than the mortality group among patients with TBI. Additionally, logistic regression analysis showed that increased calorie supply was associated with reduced mortality in patients with non-severe TBI. The mortality group had low protein intake; however, this did not emerge as a risk factor for mortality. Early sufficient nutritional support improves the prognosis of patients with TBI.

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: Limited data are available on the mortality rates of patients receiving extracorporeal membrane oxygenation (ECMO) support for coronavirus disease 2019 (COVID-19). We aimed to analyze the relationship between COVID-19 and clinical outcomes for patients receiving ECMO. Methods: We retrospectively investigated patients with COVID-19 pneumonia requiring ECMO in 19 hospitals across Korea from January 1, 2020 to August 31, 2021. The primary outcome was the 90-day mortality after ECMO initiation. We performed multivariate analysis using a logistic regression model to estimate the odds ratio (OR) of 90-day mortality. Survival differences were analyzed using the Kaplan–Meier (KM) method. Results: Of 127 patients with COVID-19 pneumonia who received ECMO, 70 patients (55.1%) died within 90 days of ECMO initiation. The median age was 64 years, and 63% of patients were male. The incidence of ECMO was increased with age but was decreased after 70 years of age. However, the survival rate was decreased linearly with age. In multivariate analysis, age (OR, 1.048; 95% confidence interval [CI], 1.010–1.089; P = 0.014) and receipt of continuous renal replacement therapy (CRRT) (OR, 3.069; 95% CI, 1.312–7.180; P = 0.010) were significantly associated with an increased risk of 90-day mortality. KM curves showed significant differences in survival between groups according to age (65 years) (log-rank P = 0.021) and receipt of CRRT (log-rank P = 0.004). Conclusion Older age and receipt of CRRT were associated with higher mortality rates among patients with COVID-19 who received ECMO.

Background: In Korea, during the early phase of the coronavirus disease 2019 (COVID-19) pandemic, we responded to the uncertainty of treatments under various conditions, consistently playing catch up with the speed of evidence updates. Therefore, there was high demand for national-level evidence-based clinical practice guidelines for clinicians in a timely manner. We developed evidence-based and updated living recommendations for clinicians through a transparent development process and multidisciplinary expert collaboration. Methods: The National Evidence-based Healthcare Collaborating Agency (NECA) and the Korean Academy of Medical Sciences (KAMS) collaborated to develop trustworthy Korean living guidelines. The NECA-supported methodological sections and 8 professional medical societies of the KAMS worked with clinical experts, and 31 clinicians were involved annually. We developed a total of 35 clinical questions, including medications, respiratory/critical care, pediatric care, emergency care, diagnostic tests, and radiological examinations. Results: An evidence-based search for treatments began in March 2021 and monthly updates were performed. It was expanded to other areas, and the search interval was organized by a steering committee owing to priority changes. Evidence synthesis and recommendation review was performed by researchers, and living recommendations were updated within 3–4 months. Conclusion We provided timely recommendations on living schemes and disseminated them to the public, policymakers and various stakeholders using webpages and social media.Although the output was successful, there were some limitations. The rigor of development issues, urgent timelines for public dissemination, education for new developers, and spread of several new COVID-19 variants have worked as barriers. Therefore, we must prepare systematic processes and funding for future pandemics.