Background/Aims: This study aimed to evaluate the performance of the Model for End-Stage Liver Disease (MELD) 3.0 for predicting mortality and liver-related complications compared with the Child-Pugh classification, albumin-bilirubin (ALBI) grade, the MELD, and the MELD sodium (MELDNa) score. Methods: We evaluated a multicenter retrospective cohort of incorporated patients with cirrhosis between 2013 and 2019. We conducted comparisons of the area under the receiver operating characteristic curve (AUROC) of the MELD3.0 and other models for predicting 3-month mortality. Additionally, we assessed the risk of cirrhosis-related complications according to the MELD3.0 score. Results: A total of 3,314 patients were included. The mean age was 55.9±11.3 years, and 70.2% of the patients were male. Within the initial 3 months, 220 patients (6.6%) died, and the MELD3.0had the best predictive performance among the tested models, with an AUROC of 0.851, outperforming the Child-Pugh classification, ALBI grade, MELD, and MELDNa. A high MELD3.0score was associated with an increased risk of mortality. Compared with that of the group with a MELD3.0 score <10 points, the adjusted hazard ratio of the group with a score of 10–20 pointswas 2.176, and that for the group with a score of ≥20 points was 4.892. Each 1-point increase inthe MELD3.0 score increased the risk of cirrhosis-related complications by 1.033-fold. The risk of hepatorenal syndrome showed the highest increase, with an adjusted hazard ratio of 1.149, followed by hepatic encephalopathy and ascites. Conclusions The MELD3.0 demonstrated robust prognostic performance in predicting mortality in patients with cirrhosis. Moreover, the MELD3.0 score was linked to cirrhosis-related complications, particularly those involving kidney function, such as hepatorenal syndrome and ascites.

Background/Aims: This study aimed to evaluate the performance of the Model for End-Stage Liver Disease (MELD) 3.0 for predicting mortality and liver-related complications compared with the Child-Pugh classification, albumin-bilirubin (ALBI) grade, the MELD, and the MELD sodium (MELDNa) score. Methods: We evaluated a multicenter retrospective cohort of incorporated patients with cirrhosis between 2013 and 2019. We conducted comparisons of the area under the receiver operating characteristic curve (AUROC) of the MELD3.0 and other models for predicting 3-month mortality. Additionally, we assessed the risk of cirrhosis-related complications according to the MELD3.0 score. Results: A total of 3,314 patients were included. The mean age was 55.9±11.3 years, and 70.2% of the patients were male. Within the initial 3 months, 220 patients (6.6%) died, and the MELD3.0had the best predictive performance among the tested models, with an AUROC of 0.851, outperforming the Child-Pugh classification, ALBI grade, MELD, and MELDNa. A high MELD3.0score was associated with an increased risk of mortality. Compared with that of the group with a MELD3.0 score <10 points, the adjusted hazard ratio of the group with a score of 10–20 pointswas 2.176, and that for the group with a score of ≥20 points was 4.892. Each 1-point increase inthe MELD3.0 score increased the risk of cirrhosis-related complications by 1.033-fold. The risk of hepatorenal syndrome showed the highest increase, with an adjusted hazard ratio of 1.149, followed by hepatic encephalopathy and ascites. Conclusions The MELD3.0 demonstrated robust prognostic performance in predicting mortality in patients with cirrhosis. Moreover, the MELD3.0 score was linked to cirrhosis-related complications, particularly those involving kidney function, such as hepatorenal syndrome and ascites.

Background/Aims: This study aimed to evaluate the performance of the Model for End-Stage Liver Disease (MELD) 3.0 for predicting mortality and liver-related complications compared with the Child-Pugh classification, albumin-bilirubin (ALBI) grade, the MELD, and the MELD sodium (MELDNa) score. Methods: We evaluated a multicenter retrospective cohort of incorporated patients with cirrhosis between 2013 and 2019. We conducted comparisons of the area under the receiver operating characteristic curve (AUROC) of the MELD3.0 and other models for predicting 3-month mortality. Additionally, we assessed the risk of cirrhosis-related complications according to the MELD3.0 score. Results: A total of 3,314 patients were included. The mean age was 55.9±11.3 years, and 70.2% of the patients were male. Within the initial 3 months, 220 patients (6.6%) died, and the MELD3.0had the best predictive performance among the tested models, with an AUROC of 0.851, outperforming the Child-Pugh classification, ALBI grade, MELD, and MELDNa. A high MELD3.0score was associated with an increased risk of mortality. Compared with that of the group with a MELD3.0 score <10 points, the adjusted hazard ratio of the group with a score of 10–20 pointswas 2.176, and that for the group with a score of ≥20 points was 4.892. Each 1-point increase inthe MELD3.0 score increased the risk of cirrhosis-related complications by 1.033-fold. The risk of hepatorenal syndrome showed the highest increase, with an adjusted hazard ratio of 1.149, followed by hepatic encephalopathy and ascites. Conclusions The MELD3.0 demonstrated robust prognostic performance in predicting mortality in patients with cirrhosis. Moreover, the MELD3.0 score was linked to cirrhosis-related complications, particularly those involving kidney function, such as hepatorenal syndrome and ascites.

Background/Aims: This study aimed to evaluate the performance of the Model for End-Stage Liver Disease (MELD) 3.0 for predicting mortality and liver-related complications compared with the Child-Pugh classification, albumin-bilirubin (ALBI) grade, the MELD, and the MELD sodium (MELDNa) score. Methods: We evaluated a multicenter retrospective cohort of incorporated patients with cirrhosis between 2013 and 2019. We conducted comparisons of the area under the receiver operating characteristic curve (AUROC) of the MELD3.0 and other models for predicting 3-month mortality. Additionally, we assessed the risk of cirrhosis-related complications according to the MELD3.0 score. Results: A total of 3,314 patients were included. The mean age was 55.9±11.3 years, and 70.2% of the patients were male. Within the initial 3 months, 220 patients (6.6%) died, and the MELD3.0had the best predictive performance among the tested models, with an AUROC of 0.851, outperforming the Child-Pugh classification, ALBI grade, MELD, and MELDNa. A high MELD3.0score was associated with an increased risk of mortality. Compared with that of the group with a MELD3.0 score <10 points, the adjusted hazard ratio of the group with a score of 10–20 pointswas 2.176, and that for the group with a score of ≥20 points was 4.892. Each 1-point increase inthe MELD3.0 score increased the risk of cirrhosis-related complications by 1.033-fold. The risk of hepatorenal syndrome showed the highest increase, with an adjusted hazard ratio of 1.149, followed by hepatic encephalopathy and ascites. Conclusions The MELD3.0 demonstrated robust prognostic performance in predicting mortality in patients with cirrhosis. Moreover, the MELD3.0 score was linked to cirrhosis-related complications, particularly those involving kidney function, such as hepatorenal syndrome and ascites.

Objective: This study aimed to evaluate the diagnostic performance and procedural characteristics of fluoroscopy-guided percutaneous transthoracic pleural forceps biopsy (PTPFB) in patients with exudative pleural effusion. Materials and Methods: Patients with exudative pleural effusion who underwent PTPFB between May 1, 2014, and February 28, 2023, were included in this retrospective study. The interval between percutaneous catheter drainage (PCD) and PTPFB, number of biopsies, procedural time, and procedure-related complications were evaluated. The sensitivity, specificity, and accuracy of diagnosing malignancy were computed for pleural cytology using PCD drainage, PTPFB, and combined PTPFB and pleural cytology. Results: Seventy-one patients, comprising 50 male and 21 female (mean age, 69.5 ± 15.3 years), were included in this study.The final diagnoses were benign lesions in 48 patients (67.6%) and malignant in 23 patients (32.4%). The overall interval between PCD and biopsy was 2.4 ± 3.7 days. The interval between PCD and biopsy in the group that underwent delayed PTPFB was 5.2 ± 3.9 days. The mean number of biopsies was 4.5 ± 1.3. The mean procedural time was 4.4 ± 2.1 minutes. Minor bleeding complications were reported in one patient (1.4%). The sensitivity, specificity, and accuracy for pleural cytology, PTPFB, and combined PTPFB and pleural cytology were 47.8% (11/23), 100% (48/48), and 83.1% (59/71), respectively;65.2% (15/23), 100% (48/48), and 88.7% (63/71), respectively; and 78.3% (18/23), 100% (48/48), and 93.0% (66/71), respectively. The sensitivity and accuracy of cytology combined with PTPFB were significantly higher than those of cytological testing alone (P = 0.008 and 0.001, respectively). Conclusion Fluoroscopy-guided PTPFB is an accurate and safe diagnostic technique for patients with exudative pleural effusion, with acceptable diagnostic performance, low complication rates, and reasonable procedural times.

Objectives: ：This study aims to explore the prevalence of depressive symptoms among elderly residents in the relatively stable rural areas of Jeju and to examine the relationships between levels of depression, sociodemographic factors, and health habits. Methods: ：The study site was within rural Jeju, where elderly individuals aged 65 and older were randomly selected from the ‘Agricultural Cohort’ registered at the Centers for Farmers` Safety and Health Center. Trainedinterviewers conducted surveys using the Short Form Geriatric Depression Scale (sGDS-K), defining those withscores of 6 or above as experiencing depressive symptoms for the analysis. Other variables such as sex, age, educational level, marital status, annual income, subjective health status, underlying disease, perceived stress levels, smoking, and drinking status were also recorded Results：Out of 533 subjects, the prevalence of depressive symptoms was 35.3%, with 28.5% in male and 45.6%in female (p<0.001). Factors significantly associated with the prevalence of depressive symptoms included maritalstatus (p=0.014), educational level (p<0.001), annual income (p=0.034), subjective health status (p<0.001), perceived stress level (p<0.001), feeling of despair (p<0.001) and suicidal ideas (p<0.001). Multivariate logistic regression analysis revealed that subjective health status, perceived stress level, and feelings of despair were associated with the prevalence of depressive symptoms. Conclusions ：The high prevalence of depressive symptoms among the rural elderly in Jeju highlights the need for targeted mental health interventions. Addressing sociocultural factors and improving early detection and intervention strategies can help reduce the socioeconomic impact of depression in this population.

Objectives: ：This study aims to explore the prevalence of depressive symptoms among elderly residents in the relatively stable rural areas of Jeju and to examine the relationships between levels of depression, sociodemographic factors, and health habits. Methods: ：The study site was within rural Jeju, where elderly individuals aged 65 and older were randomly selected from the ‘Agricultural Cohort’ registered at the Centers for Farmers` Safety and Health Center. Trainedinterviewers conducted surveys using the Short Form Geriatric Depression Scale (sGDS-K), defining those withscores of 6 or above as experiencing depressive symptoms for the analysis. Other variables such as sex, age, educational level, marital status, annual income, subjective health status, underlying disease, perceived stress levels, smoking, and drinking status were also recorded Results：Out of 533 subjects, the prevalence of depressive symptoms was 35.3%, with 28.5% in male and 45.6%in female (p<0.001). Factors significantly associated with the prevalence of depressive symptoms included maritalstatus (p=0.014), educational level (p<0.001), annual income (p=0.034), subjective health status (p<0.001), perceived stress level (p<0.001), feeling of despair (p<0.001) and suicidal ideas (p<0.001). Multivariate logistic regression analysis revealed that subjective health status, perceived stress level, and feelings of despair were associated with the prevalence of depressive symptoms. Conclusions ：The high prevalence of depressive symptoms among the rural elderly in Jeju highlights the need for targeted mental health interventions. Addressing sociocultural factors and improving early detection and intervention strategies can help reduce the socioeconomic impact of depression in this population.

Objectives: ：This study aims to explore the prevalence of depressive symptoms among elderly residents in the relatively stable rural areas of Jeju and to examine the relationships between levels of depression, sociodemographic factors, and health habits. Methods: ：The study site was within rural Jeju, where elderly individuals aged 65 and older were randomly selected from the ‘Agricultural Cohort’ registered at the Centers for Farmers` Safety and Health Center. Trainedinterviewers conducted surveys using the Short Form Geriatric Depression Scale (sGDS-K), defining those withscores of 6 or above as experiencing depressive symptoms for the analysis. Other variables such as sex, age, educational level, marital status, annual income, subjective health status, underlying disease, perceived stress levels, smoking, and drinking status were also recorded Results：Out of 533 subjects, the prevalence of depressive symptoms was 35.3%, with 28.5% in male and 45.6%in female (p<0.001). Factors significantly associated with the prevalence of depressive symptoms included maritalstatus (p=0.014), educational level (p<0.001), annual income (p=0.034), subjective health status (p<0.001), perceived stress level (p<0.001), feeling of despair (p<0.001) and suicidal ideas (p<0.001). Multivariate logistic regression analysis revealed that subjective health status, perceived stress level, and feelings of despair were associated with the prevalence of depressive symptoms. Conclusions ：The high prevalence of depressive symptoms among the rural elderly in Jeju highlights the need for targeted mental health interventions. Addressing sociocultural factors and improving early detection and intervention strategies can help reduce the socioeconomic impact of depression in this population.

Objectives: ：This study aims to explore the prevalence of depressive symptoms among elderly residents in the relatively stable rural areas of Jeju and to examine the relationships between levels of depression, sociodemographic factors, and health habits. Methods: ：The study site was within rural Jeju, where elderly individuals aged 65 and older were randomly selected from the ‘Agricultural Cohort’ registered at the Centers for Farmers` Safety and Health Center. Trainedinterviewers conducted surveys using the Short Form Geriatric Depression Scale (sGDS-K), defining those withscores of 6 or above as experiencing depressive symptoms for the analysis. Other variables such as sex, age, educational level, marital status, annual income, subjective health status, underlying disease, perceived stress levels, smoking, and drinking status were also recorded Results：Out of 533 subjects, the prevalence of depressive symptoms was 35.3%, with 28.5% in male and 45.6%in female (p<0.001). Factors significantly associated with the prevalence of depressive symptoms included maritalstatus (p=0.014), educational level (p<0.001), annual income (p=0.034), subjective health status (p<0.001), perceived stress level (p<0.001), feeling of despair (p<0.001) and suicidal ideas (p<0.001). Multivariate logistic regression analysis revealed that subjective health status, perceived stress level, and feelings of despair were associated with the prevalence of depressive symptoms. Conclusions ：The high prevalence of depressive symptoms among the rural elderly in Jeju highlights the need for targeted mental health interventions. Addressing sociocultural factors and improving early detection and intervention strategies can help reduce the socioeconomic impact of depression in this population.