Vertebral arteriovenous fistula (VAVF) is a rare lesion characterized by an abnormal connection between the extracranial vertebral artery and the surrounding venous plexus. It typically arises due to penetrating injury, although it can occasionally result from blunt trauma. Brachial plexus injury (BPI) is also infrequently associated with VAVF. We present a rare case of VAVF caused by blunt trauma, which resulted in BPI. The patient, who had previously sustained a C2 fracture and C2–3 myelopathy from a bicycle accident, presented with new-onset weakness in the right upper extremity. His previous clinical history led to an initial suspicion of either an exacerbation of a pre-existing lesion or a shoulder injury. However, electromyography indicated that the weakness was due to BPI. Further evaluations later revealed VAVF to be the primary cause of the BPI. VAVF must be recognized as a rare potential reason for BPI, as timely intervention is essential for improving patient recovery and prognosis.

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.

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.

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: 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.