Successful liberation from mechanical ventilation is one of the most crucial processes in critical care because it is the first step by which a respiratory failure patient begins to transition out of the intensive care unit and return to their own life. Therefore, when devising appropriate strategies for removing mechanical ventilation, it is essential to consider not only the individual experiences of healthcare professionals, but also scientific and systematic approaches. Recently, numerous studies have investigated methods and tools for identifying when mechanically ventilated patients are ready to breathe on their own. The Korean Society of Critical Care Medicine therefore provides these recommendations to clinicians about liberation from the ventilator. Methods: Meta-analyses and comprehensive syntheses were used to thoroughly review, compile, and summarize the complete body of relevant evidence. All studies were meticulously assessed using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) method, and the outcomes were presented succinctly as evidence profiles. Those evidence syntheses were discussed by a multidisciplinary committee of experts in mechanical ventilation, who then developed and approved recommendations. Results: Recommendations for nine PICO (population, intervention, comparator, and outcome) questions about ventilator liberation are presented in this document. This guideline includes seven conditional recommendations, one expert consensus recommendation, and one conditional deferred recommendation. Conclusions: We developed these clinical guidelines for mechanical ventilation liberation to provide meaningful recommendations. These guidelines reflect the best treatment for patients seeking liberation from mechanical ventilation.

Successful liberation from mechanical ventilation is one of the most crucial processes in critical care because it is the first step by which a respiratory failure patient begins to transition out of the intensive care unit and return to their own life. Therefore, when devising appropriate strategies for removing mechanical ventilation, it is essential to consider not only the individual experiences of healthcare professionals, but also scientific and systematic approaches. Recently, numerous studies have investigated methods and tools for identifying when mechanically ventilated patients are ready to breathe on their own. The Korean Society of Critical Care Medicine therefore provides these recommendations to clinicians about liberation from the ventilator. Methods: Meta-analyses and comprehensive syntheses were used to thoroughly review, compile, and summarize the complete body of relevant evidence. All studies were meticulously assessed using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) method, and the outcomes were presented succinctly as evidence profiles. Those evidence syntheses were discussed by a multidisciplinary committee of experts in mechanical ventilation, who then developed and approved recommendations. Results: Recommendations for nine PICO (population, intervention, comparator, and outcome) questions about ventilator liberation are presented in this document. This guideline includes seven conditional recommendations, one expert consensus recommendation, and one conditional deferred recommendation. Conclusions: We developed these clinical guidelines for mechanical ventilation liberation to provide meaningful recommendations. These guidelines reflect the best treatment for patients seeking liberation from mechanical ventilation.

Successful liberation from mechanical ventilation is one of the most crucial processes in critical care because it is the first step by which a respiratory failure patient begins to transition out of the intensive care unit and return to their own life. Therefore, when devising appropriate strategies for removing mechanical ventilation, it is essential to consider not only the individual experiences of healthcare professionals, but also scientific and systematic approaches. Recently, numerous studies have investigated methods and tools for identifying when mechanically ventilated patients are ready to breathe on their own. The Korean Society of Critical Care Medicine therefore provides these recommendations to clinicians about liberation from the ventilator. Methods: Meta-analyses and comprehensive syntheses were used to thoroughly review, compile, and summarize the complete body of relevant evidence. All studies were meticulously assessed using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) method, and the outcomes were presented succinctly as evidence profiles. Those evidence syntheses were discussed by a multidisciplinary committee of experts in mechanical ventilation, who then developed and approved recommendations. Results: Recommendations for nine PICO (population, intervention, comparator, and outcome) questions about ventilator liberation are presented in this document. This guideline includes seven conditional recommendations, one expert consensus recommendation, and one conditional deferred recommendation. Conclusions: We developed these clinical guidelines for mechanical ventilation liberation to provide meaningful recommendations. These guidelines reflect the best treatment for patients seeking liberation from mechanical ventilation.

Successful liberation from mechanical ventilation is one of the most crucial processes in critical care because it is the first step by which a respiratory failure patient begins to transition out of the intensive care unit and return to their own life. Therefore, when devising appropriate strategies for removing mechanical ventilation, it is essential to consider not only the individual experiences of healthcare professionals, but also scientific and systematic approaches. Recently, numerous studies have investigated methods and tools for identifying when mechanically ventilated patients are ready to breathe on their own. The Korean Society of Critical Care Medicine therefore provides these recommendations to clinicians about liberation from the ventilator. Methods: Meta-analyses and comprehensive syntheses were used to thoroughly review, compile, and summarize the complete body of relevant evidence. All studies were meticulously assessed using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) method, and the outcomes were presented succinctly as evidence profiles. Those evidence syntheses were discussed by a multidisciplinary committee of experts in mechanical ventilation, who then developed and approved recommendations. Results: Recommendations for nine PICO (population, intervention, comparator, and outcome) questions about ventilator liberation are presented in this document. This guideline includes seven conditional recommendations, one expert consensus recommendation, and one conditional deferred recommendation. Conclusions: We developed these clinical guidelines for mechanical ventilation liberation to provide meaningful recommendations. These guidelines reflect the best treatment for patients seeking liberation from mechanical ventilation.

Objectives: Sepsis is a leading global cause of mortality, and predicting its outcomes is vital for improving patient care. This study explored the capabilities of ChatGPT, a state-of-the-art natural language processing model, in predicting in-hospital mortality for sepsis patients. Methods: This study utilized data from the Korean Sepsis Alliance (KSA) database, collected between 2019 and 2021, focusing on adult intensive care unit (ICU) patients and aiming to determine whether ChatGPT could predict all-cause mortality after ICU admission at 7 and 30 days. Structured prompts enabled ChatGPT to engage in in-context learning, with the number of patient examples varying from zero to six. The predictive capabilities of ChatGPT-3.5-turbo and ChatGPT-4 were then compared against a gradient boosting model (GBM) using various performance metrics. Results: From the KSA database, 4,786 patients formed the 7-day mortality prediction dataset, of whom 718 died, and 4,025 patients formed the 30-day dataset, with 1,368 deaths. Age and clinical markers (e.g., Sequential Organ Failure Assessment score and lactic acid levels) showed significant differences between survivors and non-survivors in both datasets. For 7-day mortality predictions, the area under the receiver operating characteristic curve (AUROC) was 0.70–0.83 for GPT-4, 0.51–0.70 for GPT-3.5, and 0.79 for GBM. The AUROC for 30-day mortality was 0.51–0.59 for GPT-4, 0.47–0.57 for GPT-3.5, and 0.76 for GBM. Zero-shot predictions using GPT-4 for mortality from ICU admission to day 30 showed AUROCs from the mid-0.60s to 0.75 for GPT-4 and mainly from 0.47 to 0.63 for GPT-3.5. Conclusions GPT-4 demonstrated potential in predicting short-term in-hospital mortality, although its performance varied across different evaluation metrics.

Background: Successful liberation from mechanical ventilation is one of the most crucial processes in critical care, because it is the first step through which a respiratory failure patient begins to transition out of the intensive care unit, and return to normal life. Therefore, when devising appropriate strategies for removing mechanical ventilation, it is essential to consider scientific and systematic approaches, as well as the individual experiences of healthcare professionals. Recently, numerous studies have investigated methods and tools to identify when mechanically ventilated patients are ready to breathe on their own. The Korean Society of Critical Care Medicine therefore provides these recommendations to clinicians for liberation from the ventilator. Methods: Meta-analyses and comprehensive syntheses were used to thoroughly review, compile, and summarize the complete body of relevant evidence. All studies were meticulously assessed using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) method, and the outcomes were presented succinctly as evidence profiles. These evidence syntheses were discussed by a multidisciplinary committee of experts in mechanical ventilation, who then developed and approved the recommendations. Results: Recommendations for nine questions on ventilator liberation about Population, Intervention, Comparator, and Outcome (PICO) are presented in this document. This guideline presents seven conditional recommendations, one expert consensus recommendation, and one conditional deferred recommendation. Conclusion We developed these clinical guidelines for mechanical ventilation liberation to provide meaningful recommendations. These guidelines reflect the best treatment for patients seeking liberation from mechanical ventilation.

The process of cancer metastasis is dependent on the cancer cells’ capacity to detach from the primary tumor, endure in a suspended state, and establish colonies in other locations.Anchorage dependence, which refers to the cells’ reliance on attachment to the extracellular matrix (ECM), is a critical determinant of cellular shape, dynamics, behavior, and, ultimately, cell fate in nonmalignant and cancer cells. Anchorage-independent growth is a characteristic feature of cells resistant to anoikis, a programmed cell death process triggered by detachment from the ECM. This ability to grow and survive without attachment to a substrate is a crucial stage in the progression of metastasis. The recently discovered phenomenon named “adherent-to-suspension transition (AST)” alters the requirement for anchoring and enhances survival in a suspended state. AST is controlled by four transcription factors (IKAROS family zinc finger 1, nuclear factor erythroid 2, BTG anti-proliferation factor 2, and interferon regulatory factor 8) and can detach cells without undergoing the typical epithelialmesenchymal transition. Notably, AST factors are highly expressed in circulating tumor cells compared to their attached counterparts, indicating their crucial role in the spread of cancer.Crucially, the suppression of AST substantially reduces metastasis while sparing primary tumors. These findings open up possibilities for developing targeted therapies that inhibit metastasis and emphasize the importance of AST, leading to a fundamental change in our comprehension of how cancer spreads.

Background: Current international guidelines recommend against deep sedation as it is associated with worse outcomes in the intensive care unit (ICU). However, in Korea the prevalence of deep sedation and its impact on patients in the ICU are not well known. Methods: From April 2020 to July 2021, a multicenter, prospective, longitudinal, noninterventional cohort study was performed in 20 Korean ICUs. Sedation depth extent was divided into light and deep using a mean Richmond Agitation–Sedation Scale value within the first 48 hours. Propensity score matching was used to balance covariables; the outcomes were compared between the two groups. Results: Overall, 631 patients (418 [66.2%] and 213 [33.8%] in the deep and light sedation groups, respectively) were included. Mortality rates were 14.1% and 8.4% in the deep and light sedation groups (P = 0.039), respectively. Kaplan-Meier estimates showed that time to extubation (P < 0.001), ICU length of stay (P = 0.005), and death P = 0.041) differed between the groups. After adjusting for confounders, early deep sedation was only associated with delayed time to extubation (hazard ratio [HR], 0.66; 95% confidence inter val [CI], 0.55– 0.80; P < 0.001). In the matched cohort, deep sedation remained significantly associated with delayed time to extubation (HR, 0.68; 95% 0.56–0.83; P < 0.001) but was not associated with ICU length of stay (HR, 0.94; 95% CI, 0.79–1.13; P = 0.500) and in-hospital mortality (HR, 1.19; 95% CI, 0.65–2.17; P = 0.582). Conclusion In many Korean ICUs, early deep sedation was highly prevalent in mechanically ventilated patients and was associated with delayed extubation, but not prolonged ICU stay or in-hospital death.

Background: Administration of adequate antibiotics is crucial for better outcomes in sepsis. Because no uniform tool can accurately assess the risk of multidrug-resistant (MDR) pathogens, a local antibiogram is necessary. We aimed to describe the antibiogram of MDR bacteria based on locations of sepsis onset in South Korea. Methods: We performed a prospective observational study of adult patients diagnosed with sepsis according to Sepsis-3 from 19 institutions (13 tertiary referral and 6 universityaffiliated general hospitals) in South Korea. Patients were divided into four groups based on the respective location of sepsis onset: community, nursing home, long-term-care hospital, and hospital. Along with the antibiogram, risk factors of MDR bacteria and drug-bug match of empirical antibiotics were analyzed. Results: MDR bacteria were detected in 1,596 (22.7%) of 7,024 patients with gram-negative predominance. MDR gram-negative bacteria were more commonly detected in long-termcare hospital- (30.4%) and nursing home-acquired (26.3%) sepsis, whereas MDR grampositive bacteria were more prevalent in hospital-acquired (10.9%) sepsis. Such findings were consistent regardless of the location and tier of hospitals throughout South Korea. Patients with long-term-care hospital-acquired sepsis had the highest risk of MDR pathogen, which was even higher than those with hospital-acquired sepsis (adjusted odds ratio, 1.42; 95% confidence interval, 1.15–1.75) after adjustment of risk factors. The drug-bug match was lowest in patients with long-term-care hospital-acquired sepsis (66.8%). Conclusion Gram-negative MDR bacteria were more common in nursing home- and long-term-care hospital-acquired sepsis, whereas gram-positive MDR bacteria were more common in hospital-acquired settings in South Korea. Patients with long-term-care hospitalacquired sepsis had the highest the risk of MDR bacteria but lowest drug-bug match of initial antibiotics. We suggest that initial antibiotics be carefully selected according to the onset location in each patient.

Purpose: Eph receptors are differentially expressed in numerous malignant tumors. This study intended to analyze the roles of EphB receptors (EphB2, B3, and B4) in urinary bladder cancer. Materials and Methods: Tissue microarray-based immunohistochemical analysis was used to investigate the expression patterns of EphB2, EphB3, and EphB4 in 154 bladder cancer specimens. Immunohistochemical staining was conducted examining the extent of stained cells and staining intensity. EphB was considered to be highly expressed when the intensity of staining was more than moderate in >25% of cells in the tissue section. Small interfering RNA (siRNA) was used to knock down EphB expression in bladder cancer cell lines (T24, 5637) to determine the effects of EphB on tumor cell invasion, proliferation, and migration. Results: EphB receptors (B2, B3, and B4) were detected in 40.9% (EphB2, 63/154), 71.4% (EphB3, 110/154), and 53.2% (EphB4, 82/154) of bladder cancer specimens. Low expression of EphB2, B3, and B4 receptors were significantly associated with higher tumor grade (EphB2, p<0.001; EphB3, p=0.032; EphB4, p<0.001) and muscular invasion (EphB2, p=0.002; EphB3, p=0.009; EphB4, p<0.001). No obvious correlation was observed with other clinicopathological variables, such as age, sex, recurrence, lymph node involvement, metastasis, and overall survival. Inactivation of EphB receptors by siRNA transfection increased cell viability, tumor cell invasion, proliferation, and migration in comparison with untransfected cancer cells. Conclusion Low expression of EphB receptors (B2, B3, and B4) can be a predictive marker for muscular invasion of bladder cancer.