Background: An ideal lung allocation system should reduce waiting list deaths, improve transplant survival, and ensure equitable organ allocation. This study aimed to develop a novel lung allocation score (LAS) system, the MaxBenefit LAS, to maximize transplant benefits. Methods: This study retrospectively analyzed data from the Korean Network for Organ Sharing database, including 1,599 lung transplant candidates between September 2009 and December 2020. We developed the MaxBenefit LAS, combining a waitlist mortality model and a post-transplant survival model using elastic-net Cox regression, was assessed using area under the curve (AUC) values and Uno’s C-index. Its performance was compared to the US LAS in an independent cohort. Results: The waitlist mortality model showed strong predictive performance with AUC values of 0.834 and 0.818 in the training and validation cohorts, respectively. The post-transplant survival model also demonstrated good predictive ability (AUC: 0.708 and 0.685). The MaxBenefit LAS effectively stratified patients by risk, with higher scores correlating with increased waitlist mortality and decreased post-transplant mortality. The MaxBenefit LAS outperformed the conventional LAS in predicting waitlist death and identifying candidates with higher transplant benefits. Conclusion The MaxBenefit LAS offers a promising approach to optimizing lung allocation by balancing the urgency of candidates with their likelihood of survival post-transplant. This novel system has the potential to improve outcomes for lung transplant recipients and reduce waitlist mortality, providing a more equitable allocation of donor lungs.

Background: An ideal lung allocation system should reduce waiting list deaths, improve transplant survival, and ensure equitable organ allocation. This study aimed to develop a novel lung allocation score (LAS) system, the MaxBenefit LAS, to maximize transplant benefits. Methods: This study retrospectively analyzed data from the Korean Network for Organ Sharing database, including 1,599 lung transplant candidates between September 2009 and December 2020. We developed the MaxBenefit LAS, combining a waitlist mortality model and a post-transplant survival model using elastic-net Cox regression, was assessed using area under the curve (AUC) values and Uno’s C-index. Its performance was compared to the US LAS in an independent cohort. Results: The waitlist mortality model showed strong predictive performance with AUC values of 0.834 and 0.818 in the training and validation cohorts, respectively. The post-transplant survival model also demonstrated good predictive ability (AUC: 0.708 and 0.685). The MaxBenefit LAS effectively stratified patients by risk, with higher scores correlating with increased waitlist mortality and decreased post-transplant mortality. The MaxBenefit LAS outperformed the conventional LAS in predicting waitlist death and identifying candidates with higher transplant benefits. Conclusion The MaxBenefit LAS offers a promising approach to optimizing lung allocation by balancing the urgency of candidates with their likelihood of survival post-transplant. This novel system has the potential to improve outcomes for lung transplant recipients and reduce waitlist mortality, providing a more equitable allocation of donor lungs.

Heart failure (HF) is a major cause of mortality and morbidity in South Korea, imposing substantial physical, emotional, and financial burdens on patients and society. Despite the high burden of symptom and complex care needs of HF patients, palliative care and hospice services remain underutilized in South Korea due to cultural, institutional, and knowledge-related barriers. This position statement from the Korean Society of Heart Failure emphasizes the need for integrating palliative and hospice care into HF management to improve quality of life and support holistic care for patients and their families. By clarifying the role of palliative care in HF and proposing practical referral criteria, this position statement aims to bridge the gap between HF and palliative care services in South Korea, ultimately improving patient-centered outcomes and aligning treatment with the goals and values of HF patients.

Background: An ideal lung allocation system should reduce waiting list deaths, improve transplant survival, and ensure equitable organ allocation. This study aimed to develop a novel lung allocation score (LAS) system, the MaxBenefit LAS, to maximize transplant benefits. Methods: This study retrospectively analyzed data from the Korean Network for Organ Sharing database, including 1,599 lung transplant candidates between September 2009 and December 2020. We developed the MaxBenefit LAS, combining a waitlist mortality model and a post-transplant survival model using elastic-net Cox regression, was assessed using area under the curve (AUC) values and Uno’s C-index. Its performance was compared to the US LAS in an independent cohort. Results: The waitlist mortality model showed strong predictive performance with AUC values of 0.834 and 0.818 in the training and validation cohorts, respectively. The post-transplant survival model also demonstrated good predictive ability (AUC: 0.708 and 0.685). The MaxBenefit LAS effectively stratified patients by risk, with higher scores correlating with increased waitlist mortality and decreased post-transplant mortality. The MaxBenefit LAS outperformed the conventional LAS in predicting waitlist death and identifying candidates with higher transplant benefits. Conclusion The MaxBenefit LAS offers a promising approach to optimizing lung allocation by balancing the urgency of candidates with their likelihood of survival post-transplant. This novel system has the potential to improve outcomes for lung transplant recipients and reduce waitlist mortality, providing a more equitable allocation of donor lungs.

Background: An ideal lung allocation system should reduce waiting list deaths, improve transplant survival, and ensure equitable organ allocation. This study aimed to develop a novel lung allocation score (LAS) system, the MaxBenefit LAS, to maximize transplant benefits. Methods: This study retrospectively analyzed data from the Korean Network for Organ Sharing database, including 1,599 lung transplant candidates between September 2009 and December 2020. We developed the MaxBenefit LAS, combining a waitlist mortality model and a post-transplant survival model using elastic-net Cox regression, was assessed using area under the curve (AUC) values and Uno’s C-index. Its performance was compared to the US LAS in an independent cohort. Results: The waitlist mortality model showed strong predictive performance with AUC values of 0.834 and 0.818 in the training and validation cohorts, respectively. The post-transplant survival model also demonstrated good predictive ability (AUC: 0.708 and 0.685). The MaxBenefit LAS effectively stratified patients by risk, with higher scores correlating with increased waitlist mortality and decreased post-transplant mortality. The MaxBenefit LAS outperformed the conventional LAS in predicting waitlist death and identifying candidates with higher transplant benefits. Conclusion The MaxBenefit LAS offers a promising approach to optimizing lung allocation by balancing the urgency of candidates with their likelihood of survival post-transplant. This novel system has the potential to improve outcomes for lung transplant recipients and reduce waitlist mortality, providing a more equitable allocation of donor lungs.

Background: Atopic dermatitis (AD) is a common skin disease with a wide range of symptoms. Due to the rapidly changing treatment landscape, regular updates to clinical guidelines are needed. Objective: This study aimed to update the guidelines for the treatment of AD to reflect recent therapeutic advances and evidence-based recommendations. Methods: The Patient characteristics, type of Intervention, Control, and Outcome framework was used to determine 48 questions related to AD management. Evidence was graded, recommendations were determined, and, after 2 voting rounds among the Korean Atopic Dermatitis Association (KADA) council members, consensus was achieved. Results: This guideline provides treatment guidance on advanced systemic treatment modalities for AD. In particular, the guideline offers up-to-date treatment recommendations for biologics and Janus-kinase inhibitors used in the treatment of patients with moderate to severe AD.It also provides guidance on other therapies for AD, along with tailored recommendations for children, adolescents, the elderly, and pregnant or breastfeeding women. Conclusion KADA’s updated AD treatment guidelines incorporate the latest evidence and expert opinion to provide a comprehensive approach to AD treatment. The guidelines will help clinicians optimize patient-specific therapies.

Background: Atopic dermatitis (AD) is a common skin disease with a wide range of symptoms. Due to the rapidly changing treatment landscape, regular updates to clinical guidelines are needed. Objective: This study aimed to update the guidelines for the treatment of AD to reflect recent therapeutic advances and evidence-based practices. Methods: The Patient characteristics, type of Intervention, Control, and Outcome framework was used to determine 48 questions related to AD management. Evidence was graded, recommendations were determined, and, after 2 voting rounds among the Korean Atopic Dermatitis Association (KADA) council members, consensus was achieved. Results: The guidelines provide detailed recommendations on foundational therapies, including the use of moisturizers, cleansing and bathing practices, allergen avoidance, and patient education. Guidance on topical therapies, such as topical corticosteroids and calcineurin inhibitors, is also provided to help manage inflammation and maintain skin barrier function in patients with AD. Additionally, recommendations on conventional systemic therapies, including corticosteroids, cyclosporine, and methotrexate, are provided for managing moderate to severe AD. Conclusion KADA’s updated AD guidelines offer clinicians evidence-based strategies focused on basic therapies, topical therapies, and conventional systemic therapies, equipping them to enhance quality of care and improve patient outcomes in AD management.

Purpose: This study aimed to investigate the optimal withdrawal time (WT) for initial surveillance colonoscopy after curative resection for colorectal cancer (CRC) by comparing anterior/low anterior resection (AR/LAR) and right hemicolectomy (RHC) groups. Methods: This retrospective study analyzed 1,212 patients who underwent initial surveillance colonoscopy after CRC resection between 2015 and 2022. The patients were divided into the AR/LAR (n = 846) and RHC (n = 366) groups. The optimal WT was determined using receiver operating characteristic curve analysis and validated using logistic regression models. The adenoma and advanced neoplasia detection rates (ADR/ANDR) were evaluated based on the optimal WT. Results: The optimal WT was 7 and 6 minutes in the AR/LAR and RHC groups, respectively. In multivariate analysis, WT ≥7 and ≥6 minutes in the AR/LAR (odds ratio [OR], 2.38; 95% confidence interval [CI], 1.75–3.24; P < 0.001) and RHC (OR, 2.64;95% CI, 1.59–4.39; P = 0.001) groups, respectively, were significant factors for adenoma detection. In the AR/LAR group, ADR was 41.5% for WT ≥7 minutes compared to 21.9% for WT <7 minutes (P < 0.001). In the RHC group, ADR for WT ≥6 minutes was 33.9% compared to 15.8% for WT <6 minutes (P < 0.001). The ANDR also significantly improved with longer WTs in both groups. Conclusion This study suggests that a minimum WT of 7 and 6 minutes for AR/LAR and RHC patients, respectively, during the initial surveillance colonoscopy after CRC resection is optimal for maintaining a satisfactory ADR and ANDR. These findings highlight the importance of tailoring colonoscopic procedures according to the type of surgical resection.

Purpose: Current guidelines recommend endoscopic resection for rectal neuroendocrine tumors (RNETs) under 10 mm. Incomplete resections necessitate salvage procedures, highlighting the need for complete R0 resection. This study evaluates the efficacy and safety of wide hot snare polypectomy (WHSP) compared to endoscopic submucosal dissection (ESD) and endoscopic mucosal resection (EMR) for the salvage treatment of small RNETs. Methods: This retrospective study was conducted at Korea University Guro Hospital from January 2018 to December 2022. It compared the outcomes of salvage resections for RNETs ≤10 mm using 2 approaches: ESD and EMR vs. WHSP. Demographics, tumor characteristics, and clinical outcomes were compared. Efficacy was evaluated by the histological complete resection rate and procedure time, while safety was assessed by the incidence of complications. Results: Out of 135 patients undergoing salvage resection for RNET, 14 who underwent transanal excision were excluded. Of the remaining 121, 99 underwent EMR or ESD, and 22 underwent WHSP. Baseline characteristics were similar between the 2 groups. The WHSP group demonstrated a significantly higher R0 resection rate (72.7% vs. 49.5%, P = 0.010) and a shorter median procedure time (3.5 minutes vs. 8.3 minutes). No complications were reported in the WHSP group. Conclusion WHSP is a rapid, straightforward, safe, and effective approach for the salvage treatment of RNETs less than 10 mm in diameter, particularly in patients without additional risk factors.

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.