Purpose: This study aimed to explore the practices, perceptions, and barriers related to specialty palliative care (SPC) referrals among oncologists in Korea, highlighting the clinical implications of early integration. Materials and Methods: A cross-sectional online survey targeting board-certified hemato-oncology specialists was conducted between August 1-25, 2024. The survey assessed referral practices, attitudes toward early SPC integration, referral criteria, barriers, and institutional characteristics. Results: A total of 227 oncologists participated (response rate, 36.7%). Among them, 68.7% reported frequent SPC referrals, with higher referral rates observed among younger physicians, those in tertiary hospitals, and institutions with in-house SPC teams (p < 0.001). Although 74.9% supported early SPC integration, referrals were often inconsistently timed, frequently occurring after disease progression or at the discontinuation of chemotherapy. For time-based referrals, the most commonly endorsed triggers were disease progression despite palliative second-line treatment and a prognosis of expected mortality within 6-12 months. Need-based referral triggers such as patient or family requests (96.5%), psychological distress (89.9%), or uncontrolled symptoms (83.3%), were also widely endorsed. The major barriers to early SPC integration included patient and family resistance (70.0%) and limited availability of SPC teams (34.4%). Conclusion This study emphasizes the importance of systematic efforts to promote timely SPC integration in Korea, including education to raise patient awareness, improved referral systems, and enhanced infrastructure. The positive attitudes toward early SPC among oncologists reflect a growing recognition of its value, highlighting the need for strategies that align with international standards.

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.

Coronavirus disease 2019 (COVID-19) generally presents with milder illness in children and adolescents than in adults; however, infants and those with underlying chronic conditions, obesity, or immunocompromised states remain at increased risk for severe dis-ease and death. Multisystem inflammatory syndrome in children (MIS-C) affects multiple organs, including the heart, gastrointestinaltract, and skin, and can result in severe illness requiring hospitalization or death. In children and adolescents, long COVID manifests with age-dependent, heterogeneous symptoms, leading not only to persistent physical complaints but also to neurologic manifestations and mental health problems. Therefore, evidence-based clinical guidelines and approved treatments for COVID-19 in children and adolescents remain limited, and research is needed to build a pediatric evidence base. Generating high-quality data is essential to develop optimized diagnostic and therapeutic strategies, establish standardized care pathways, and ultimately improve preparedness and outcomes for children and adolescents during future emerging infectious disease outbreaks. In this clinical information article, we review the epidemiology, clinical symptoms, complications, and drug treatment of COVID-19 in the pediatric population.

Background: Lung dysfunction and high apolipoprotein B/apolipoprotein A-I (apoB/apoA-I) ratio are both recognized risk factors for cardiovascular disease. However, few studies have examined the association between the apoB/ApoA-I ratio and lung function. Therefore, we investigated whether this ratio is associated with decreased lung function in a large healthy cohort. Methods: We performed a cohort study on 68,418 healthy Koreans (34,797 males, mean age:38.1 years) who underwent a health examination in 2019. ApoB/apoA-I ratio was categorized into quartiles. Spirometric values at the fifth percentile in our population were considered the lower limit of normal (LLN), which was used to define lung function impairment. Adjusted odds ratios (aORs) and 95% confidence intervals (CIs), using the lowest quartile as the reference, were estimated to determine lung function impairment. Results: Mean apoB/apoA-I ratio was 0.67 ± 0.21. Subjects with the highest quartile of this ratio had the lowest predicted forced expiratory volume in one second (FEV1 %) and forced vital capacity (FVC%) after controlling for covariates (P < 0.001). However, FEV1 /FVC ratio was not significantly different among the four quartiles (P = 0.059). Compared with the lowest quartile (Q1, reference), the aORs (95% CI) for FEV1 % < LLN across increasing quartiles (from Q2 to Q4) were 1.216 (1.094–1.351), 1.293 (1.156–1.448), and 1.481 (1.311– 1.672) (P for trend < 0.001), respectively. Similarly, the aORs for FVC% < LLN compared with the reference were 1.212 (1.090–1.348), 1.283 (1.147–1.436), and 1.502 (1.331–1.695) with increasing quartiles (P for trend < 0.001). However, the aORs for FEV1 /FVC < LLN were not significantly different among groups (P for trend = 0.273). Conclusion High apoB/apoA-I ratio was associated with decreased lung function. However, longitudinal follow-up studies are required to validate our findings.

Plants belonging to the genus Juncus are widely distributed across North America, which are known to make a diverse array of bioactive natural products. In 2022, Juncus torreyi, a species of Juncus, was firstly found in Korea. Morphological and ecological characteristics of the species have been previously investigated;however, bioactive chemical potentials still remain to be explored. In the present work, we focused on the isolation and characterization of metabolites that harbor growth inhibitory activity against a fungal indicator, Candida albicans. Using activity-guided discovery method, we subsequently isolated and purified three metabolites from the most active methylene chloride-soluble fraction. Through NMR and high-resolution ESIOrbitrap-MS data analysis, the metabolites were structurally determined to be juncatrin B (1), ensifolin I (2), and juncusol (3). Metabolites 1–3 were evaluated for their C. albicans growth inhibitory activity and revealed inhibition with an IC 50 value of 74.3, 31.5, and 64.6 μg/mL, respectively.

Background: Pre-diabetes can develop into type 2 diabetes mellitus, but can prevented by regular exercise.However, the outcomes when combining unsupervised Kinect-based mixed-reality (KMR) exercise with continuous glucose monitoring (CGM) remain unclear. Therefore, this single-arm pilot trial examined changes in blood glucose (BG) concentrations over 672 hours (4 weeks), including a 2-week period of KMR exercise and CGM in individuals with pre-diabetes. Methods: This was a pre-and post-treatment case-control study with nine participants. General questionnaires were administered and body composition, fasting BG concentrations, and 2-hour oral glucose tolerance test (2-OGTT) results were measured pre-and post-treatment. Weekly average glucose concentrations, hyperglycemia rate, hypoglycemia rate, average glucose concentration over time, amount of physical activity, amount of food intake, and pre- and postprandial BG (immediately and 30, 60, 90, and 120 minutes after lunch) were measured over 4 weeks (pre-test, exercise, and post -test weeks). Glucose concentrations were measured before exercising, between sets, and 30 and 60 minutes after exercise during the 2 weeks of unsupervised exercise (3 days/week). Results: In all participants, body mass index (27.16±2.92 kg/m²), fasting BG (108.00±7.19 mg/dL), 2-OGTT (162.56±18.12 mg/dL), hyperglycemia rate (P= 0.040), and 90-minute postprandial BG (P= 0.035) were significantly reduced during the 2 exercise weeks, and the 2-OGTT result (P= 0.044) and diastolic blood pressure (DBP) (P= 0.046) were significantly reduced at the post- test as compared with the pre-test. Conclusion This study found that 2 weeks of unsupervised KMR exercise reduced 2-OGTT, DBP, hyperglycemia rate, and 90-minute postprandial BG concentration. We believed this effect could be identified more clearly in studies involving a larger number of participants and longer durations of exercise.

Purpose: Unnecessary prostate biopsies for detecting prostate cancer (PCa) should be minimized. Therefore, this study developed a machine learning (ML) model to predict PCa in Korean men and evaluated its usability. Materials and Methods: We retrospectively analyzed clinical data from 928 patients who underwent prostate biopsies at Kangwon National University Hospital between May 2013 and May 2023. Of these, 377 (41.6%) were diagnosed with PCa, and 551 (59.4%) did not have cancer. For external validation, clinical data from 385 patients aged 48–89 years who underwent prostate biopsies from September 2005 to September 2023 at Wonju Severance Christian Hospital were also included. Twenty-two clinical features were used to develop an ML model to predict PCa. Features were selected based on their contributions to model performance, leading to the inclusion of 15 features. A meta-learner was constructed using logistic regression to predict the probability of PCa, and the classifier was trained and validated on randomly extracted training and test sets at an 8:2 ratio. Results: The prostate health index, prostate volume, age, nodule on digital rectal examination, and prostate-specific antigen were the top 5 features for predicting PCa. The area under the receiver operating characteristic curve (AUC) of the meta-learner logistic regression model was 0.89, and the accuracy, sensitivity, and specificity were 0.828, 0.711, and 0.909, respectively. Our model also showed excellent prediction performance for high-grade PCa, with a Gleason score of 7 or higher and an AUC of 0.903. Furthermore, we evaluated the performance of the model using external cohort clinical data and achieved an AUC of 0.863. Conclusions Our ML model excelled in predicting PCa, specifically clinically significant PCa. Although extensive cross-validation in other clinical cohorts is needed, this ML model is a promising option for future diagnostics.