Objectives: Lonely death is defined as “a person living in a state of social isolation, disconnected from family, relatives, and others, who dies from suicide, illness, or other causes”. This study investigated the characteristics of individuals who die alone in Korea. Methods: We constructed a database of lonely death cases by linking data from the Korea Crime Scene Investigation Unit of the Korea National Police Agency with National Health Insurance Service (NHIS) records. A descriptive analysis was performed to evaluate the demographics, underlying diseases, and healthcare utilization patterns among lonely death cases. Results: Among the 3122 individuals identified as lonely death cases, 2621 (84.0%) were male and 501 (16.0%) were female. The most common age group was 50-59 years (n=930, 29.8%). The NHIS covered 2161 individuals (69.2%), whereas 961 individuals (30.8%) were enrolled in Medical Aid (MA). The highest number of lonely deaths occurred in Seoul areas, with 1468 cases (47.0%). Mood disorders were diagnosed in 1020 individuals (32.7%), and various alcohol-related diseases, including alcoholic liver disease, were also observed. Outpatient visits increased leading up to death but declined in the final 3 months, while hospitalizations decreased and emergency room visits slightly increased. Conclusions Most lonely death cases involved male in their 50s, with a disproportionately high number of MA beneficiaries compared to the general population. Many of these individuals also experienced mental health issues or alcohol-related disorders. Preventing social isolation and strengthening social safety nets are critical to reducing the occurrence of lonely deaths.

Objectives: Lonely death is defined as “a person living in a state of social isolation, disconnected from family, relatives, and others, who dies from suicide, illness, or other causes”. This study investigated the characteristics of individuals who die alone in Korea. Methods: We constructed a database of lonely death cases by linking data from the Korea Crime Scene Investigation Unit of the Korea National Police Agency with National Health Insurance Service (NHIS) records. A descriptive analysis was performed to evaluate the demographics, underlying diseases, and healthcare utilization patterns among lonely death cases. Results: Among the 3122 individuals identified as lonely death cases, 2621 (84.0%) were male and 501 (16.0%) were female. The most common age group was 50-59 years (n=930, 29.8%). The NHIS covered 2161 individuals (69.2%), whereas 961 individuals (30.8%) were enrolled in Medical Aid (MA). The highest number of lonely deaths occurred in Seoul areas, with 1468 cases (47.0%). Mood disorders were diagnosed in 1020 individuals (32.7%), and various alcohol-related diseases, including alcoholic liver disease, were also observed. Outpatient visits increased leading up to death but declined in the final 3 months, while hospitalizations decreased and emergency room visits slightly increased. Conclusions Most lonely death cases involved male in their 50s, with a disproportionately high number of MA beneficiaries compared to the general population. Many of these individuals also experienced mental health issues or alcohol-related disorders. Preventing social isolation and strengthening social safety nets are critical to reducing the occurrence of lonely deaths.

Objectives: Lonely death is defined as “a person living in a state of social isolation, disconnected from family, relatives, and others, who dies from suicide, illness, or other causes”. This study investigated the characteristics of individuals who die alone in Korea. Methods: We constructed a database of lonely death cases by linking data from the Korea Crime Scene Investigation Unit of the Korea National Police Agency with National Health Insurance Service (NHIS) records. A descriptive analysis was performed to evaluate the demographics, underlying diseases, and healthcare utilization patterns among lonely death cases. Results: Among the 3122 individuals identified as lonely death cases, 2621 (84.0%) were male and 501 (16.0%) were female. The most common age group was 50-59 years (n=930, 29.8%). The NHIS covered 2161 individuals (69.2%), whereas 961 individuals (30.8%) were enrolled in Medical Aid (MA). The highest number of lonely deaths occurred in Seoul areas, with 1468 cases (47.0%). Mood disorders were diagnosed in 1020 individuals (32.7%), and various alcohol-related diseases, including alcoholic liver disease, were also observed. Outpatient visits increased leading up to death but declined in the final 3 months, while hospitalizations decreased and emergency room visits slightly increased. Conclusions Most lonely death cases involved male in their 50s, with a disproportionately high number of MA beneficiaries compared to the general population. Many of these individuals also experienced mental health issues or alcohol-related disorders. Preventing social isolation and strengthening social safety nets are critical to reducing the occurrence of lonely deaths.

Patients with sensitization and blood type O experience increased waiting times for deceased-donor kidney transplantation (DDKT). While allocation benefits are needed to resolve inequity in DDKT opportunity, whether DDKT has comparable outcomes in this disadvantaged population requires further study. This study assessed these outcomes and developed a new allocation system that balances equity and utility. Methods: Patients from national and hospital cohorts from two centers in Korea were categorized as B1 to B4 (according to panel reactive antibody [PRA] positivity and ABO blood type) and A1 to A4 (based on the maximal PRA% and blood type), respectively. Competing risk and Cox regression analyses were performed to assess the effects of PRA and blood type on graft failure and mortality, respectively. Based on DDKT opportunities and posttransplant outcomes, a new scoring system for kidney allocation was developed. Results: The national and hospital cohorts included 3,311 and 819 patients, respectively, who underwent DDKT. Despite the disparities in DDKT opportunities, the graft failure rates and mortality did not differ among the different PRA and blood type groups. Furthermore, posttransplantation outcomes did not differ according to the categories with different DDKT opportunities. A new scoring system to provide additional points to disadvantaged populations was developed based on the hazard ratios for DDKT. Conclusion: A new allocation approach based on PRA and ABO blood types offers benefits to disadvantaged patients with fewer DDKT opportunities and could enhance equity without sacrificing utility in Korea, which has a long waiting time for DDKT.

Background/Aims: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a significant risk factor for cardiovascular disease. This study aimed to evaluate differences in carotid atherosclerosis and coronary artery disease severity according to MASLD subtypes using general health screening data from multiple tertiary hospitals. Methods: A total of 3,466 subjects who underwent health check-ups including abdominal ultrasound, carotid ultrasound, and cardiac computed tomography were analyzed. Participants were categorized into non-SLD, MASLD, metabolic dysfunction-associated alcohol-relat-ed liver disease (MetALD), and alcohol-related liver disease. Carotid plaque prevalence and coronary artery stenosis severity were compared across groups and stratified by fibrosis stage using the Fibrosis-4 index (FIB-4). Results: Patients with MASLD and MetALD showed a significantly higher prevalence of carotid plaques compared with the non-SLD group. The severity of coronary artery stenosis was also greater in MASLD and MetALD, particularly among those with advanced fibrosis (FIB-4 ≥2.67). Conclusions MASLD and MetALD are associated with increased burden of systemic atherosclerosis and coronary artery disease, especially in patients with advanced fibrosis. These findings highlight the importance of cardiovascular risk assessment in individuals with MASLD and its subtypes.

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: s/Aims: The hepatocellular carcinoma (HCC) with portal vein tumor thrombosis (PVTT) is classified as the advanced stage (BCLC stage C) with extremely poor prognosis, and in current guidelines is recommended for systemic therapy. This study aimed to evaluate the surgical outcomes and long-term prognosis after hepatic resection (HR) for patients who have HCC combined with PVTT. Methods: We retrospectively analyzed 332 patients who underwent HR for HCC with PVTT at ten tertiary referral hospitals in South Korea. Results: The median overall and recurrence-free survival after HR were 32.4 and 8.6 months, while the 1-, 3-, and 5-year overall survival rates were 75%, 48%, and 39%, respectively. In multivariate analysis, tumor number, tumor size, AFP, PIVKA−II, neutrophil-to-lymphocyte ratio, and albumin–bilirubin (ALBI) grade were significant prognostic factors. The risk scoring was developed using these seven factors–tumor, inflammation and hepatic function (TIF), to predict patient prognosis. The prognosis of the patients was well stratified according to the scores (log-rank test, p < 0.001). Conclusions HR for patients who have HCC combined with PVTT provided favorable survival outcomes. The risk scoring was useful in predicting prognosis, and determining the appropriate treatment strategy for those patients who have HCC with PVTT.