Limited data exist regarding the real-world practices and clinical outcomes in patients with ischemic heart failure with reduced left ventricular ejection fractions (LVEFs).Using nationwide registry data from South Korea, we aimed to investigate long-term outcomes and clinical practices, especially implantable cardioverter defibrillators (ICDs) implantation, in patients with reduced LVEFs at least 40 days after acute myocardial infarction (AMI). Of 13,056 patients with AMI between 2011 and 2015, we analyzed 350 (median age, 66 years [interquartile range, 56-75]) who had LVEFs <40% on follow-up transthoracic echocardiogram 40 days after the index event. The primary outcome was cardiac-cause mortality at 3 years. Secondary outcomes comprised major cardiovascular events as well as outcomes defined by the use of ICDs, cardiac resynchronization therapy defibrillators (CRT-Ds), and electrophysiology studies. Among 350 patients, 39 (11.1%) died from cardiac causes during 3 years of follow-up. Eleven (3.1%) were hospitalized for ventricular tachycardia. The rate of ICD or CRT-D implantation up to 3 years was 5.7% (20/350). Cox time-to-event analysis revealed older age, LVEF <30%, diabetes mellitus, and previous MI or revascularization as positively associated with cardiac death, whereas the use of statins and body weight <67 kg were negatively associated. This nationwide Korean registry demonstrated that only 5.7% of patients who had reduced LVEFs after 40 days of AMI underwent ICD implantations over 3 years. Considering the high mortality, concerted efforts are needed to improve clinical outcomes for patients who may have been candidates for ICD implantation.

Background: Human muscle satellite (stem) cells (MuSCs) are essential for investigating muscle physiology, regeneration, and disease mechanisms. Primary cultures derived directly from human tissues offer a more physiologically relevant model than immortalized cell lines. However, the isolation and characterization of MuSCs from human upper limb tissues are limited. Therefore, this study aimed to establish and characterize a primary culture system for MuSCs obtained from human upper limb muscle tissue. Methods: Human muscle tissues were obtained from upper limb surgical specimens. Muscle samples were mechanically and enzymatically dissociated to isolate muscle-derived cells, which were cultured under standard growth conditions. Cell morphology and proliferation were monitored during the culture period. Myogenic characteristics were assessed by examining the expression of muscle-specific markers including myogenic regulatory factors and structural proteins. Additionally, myogenic differentiation capacity was evaluated by inducing differentiation and analyzing the formation of multinucleated myotubes. Results: Primary MuSCs were isolated from human upper limb tissues and expanded in vitro. The cultured cells exhibited a typical spindle-shaped morphology and demonstrated significant proliferative capacity. Characterization confirmed the expression of myogenic markers, indicating the presence of muscle-derived precursor cells. Following induction of differentiation, the cells formed multinucleated myotube-like structures and expressed muscle proteins associated with differentiation, highlighting their potential for myogenic differentiation. Conclusion This study established a reliable protocol for isolating and culturing MuSCs from human upper limb tissues. Cultured cells displayed typical myogenic characteristics and differentiation capacity, indicating that this model could be a valuable platform for studying human muscle biology and potential therapeutic applications.

Coronary artery bypass grafting (CABG) remains a key revascularization strategy for ischemic heart disease; however, nationwide trends in the Republic of Korea have not been thoroughly investigated. Using data from the Korean National Health Insurance Service, we analyzed adult patients who underwent isolated CABG between 2005 and 2022. We evaluated surgical volume, patient demographics, procedural strategies (off-pump vs. onpump), and outcomes. International comparisons were conducted using national cardiac surgery registry data. A total of 51,923 CABG cases were identified. Annual surgical volume declined until 2013 but gradually increased thereafter, reaching 3,717 cases in 2022. Despite this recovery, Korea’s per capita CABG rate remains among the lowest worldwide.In contrast, more than 60% of procedures were performed off-pump—the highest rate worldwide. Over time, the average patient age and prevalence of diabetes increased, whereas in-hospital mortality showed a modest decline. Compared with other countries, the Republic of Korea demonstrated a uniquely low procedural volume and a strong preference for off-pump CABG. This nationwide analysis highlights Korea’s distinctive CABG practice patterns and provides valuable insights for optimizing future clinical and policy decisions in cardiac surgical care.

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.

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.