Radiofrequency ablation (RFA) is a minimally invasive treatment modality used as an alternative to surgery in patients with benign thyroid nodules, recurrent thyroid cancers (RTCs), and primary thyroid microcarcinomas. The Korean Society of Thyroid Radiology (KSThR) initially developed recommendations for the optimal use of RFA for thyroid tumors in 2009 and revised them in 2012 and 2017. As new meaningful evidence has accumulated since 2017 and in response to a growing global interest in the use of RFA for treating malignant thyroid lesions, the task force committee members of the KSThR decided to update the guidelines on the use of RFA for the management of RTCs based on a comprehensive analysis of current literature and expert consensus.

Purpose: Hematopoietic stem cell transplantation (HSCT) has been an important method of treatment in the advance of pediatric acute lymphoblastic leukemia (ALL). The indications for HSCT are evolving and require updated establishment. In this study, we aimed to investigate the efficacy of HSCT on the treatment outcome of pediatric ALL, considering the indications for HSCT and subgroups. Materials and Methods: A retrospective analysis was conducted on ALL patients diagnosed and treated at a single center. Risk groups were categorized based on age at diagnosis, initial white blood cell count, disease lineage (B/T), and cytogenetic study results. Data on the patients’ disease status at HSCT and indications of HSCT were collected. Indications for HSCT were categorized as upfront HSCT at 1st complete remission, relapse, and refractory disease. Results: Among the 549 screened patients, a total of 418 patients were included in the study; B-cell ALL (n=379) and T-cell ALL (T-ALL) (n=39). HSCT was conducted on a total of 106 patients (25.4%), with a higher frequency as upfront HSCT in higher-risk groups and specific cytogenetics. The overall survival (OS) was significantly better when done upfront than in relapsed or refractory state in T-ALL patients (p=0.002). The KMT2A-rearranged ALL patients showed superior event-free survival (p=0.002) and OS (p=0.022) when HSCT was done as upfront treatment. Conclusion HSCT had a substantial positive effect in a specific subset of pediatric ALL. In particular, frontline HSCT for T-ALL and KMT2A-rearranged ALL offered a better prognosis than when HSCT was conducted in a relapsed or refractory setting.

Radiofrequency ablation (RFA) is a minimally invasive treatment modality used as an alternative to surgery in patients with benign thyroid nodules, recurrent thyroid cancers (RTCs), and primary thyroid microcarcinomas. The Korean Society of Thyroid Radiology (KSThR) initially developed recommendations for the optimal use of RFA for thyroid tumors in 2009 and revised them in 2012 and 2017. As new meaningful evidence has accumulated since 2017 and in response to a growing global interest in the use of RFA for treating malignant thyroid lesions, the task force committee members of the KSThR decided to update the guidelines on the use of RFA for the management of RTCs based on a comprehensive analysis of current literature and expert consensus.

Purpose: Hematopoietic stem cell transplantation (HSCT) has been an important method of treatment in the advance of pediatric acute lymphoblastic leukemia (ALL). The indications for HSCT are evolving and require updated establishment. In this study, we aimed to investigate the efficacy of HSCT on the treatment outcome of pediatric ALL, considering the indications for HSCT and subgroups. Materials and Methods: A retrospective analysis was conducted on ALL patients diagnosed and treated at a single center. Risk groups were categorized based on age at diagnosis, initial white blood cell count, disease lineage (B/T), and cytogenetic study results. Data on the patients’ disease status at HSCT and indications of HSCT were collected. Indications for HSCT were categorized as upfront HSCT at 1st complete remission, relapse, and refractory disease. Results: Among the 549 screened patients, a total of 418 patients were included in the study; B-cell ALL (n=379) and T-cell ALL (T-ALL) (n=39). HSCT was conducted on a total of 106 patients (25.4%), with a higher frequency as upfront HSCT in higher-risk groups and specific cytogenetics. The overall survival (OS) was significantly better when done upfront than in relapsed or refractory state in T-ALL patients (p=0.002). The KMT2A-rearranged ALL patients showed superior event-free survival (p=0.002) and OS (p=0.022) when HSCT was done as upfront treatment. Conclusion HSCT had a substantial positive effect in a specific subset of pediatric ALL. In particular, frontline HSCT for T-ALL and KMT2A-rearranged ALL offered a better prognosis than when HSCT was conducted in a relapsed or refractory setting.

Radiofrequency ablation (RFA) is a minimally invasive treatment modality used as an alternative to surgery in patients with benign thyroid nodules, recurrent thyroid cancers (RTCs), and primary thyroid microcarcinomas. The Korean Society of Thyroid Radiology (KSThR) initially developed recommendations for the optimal use of RFA for thyroid tumors in 2009 and revised them in 2012 and 2017. As new meaningful evidence has accumulated since 2017 and in response to a growing global interest in the use of RFA for treating malignant thyroid lesions, the task force committee members of the KSThR decided to update the guidelines on the use of RFA for the management of RTCs based on a comprehensive analysis of current literature and expert consensus.

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.

Purpose: This study aimed to describe and understand the meaning and nature of the process of forming a therapeutic relationship among nursing students working with older patients with dementia in long-term care hospitals. Methods: In-depth interviews were conducted with 10 nursing students from September to October 2024. We examined and described the collected data based on Colaizzi's phenomenological method. Results: Seventeen theme clusters and five categories were derived from the nursing students' experiences. The five categories were as follows: preparing for scheduled encounters with unfamiliar people, embarking upon exploration to build a relationship, making various efforts to maintain a therapeutic relationship, facing obstacles in maintaining a relationship, and witnessing myself growing in a therapeutic relationship. Conclusion Efforts should be made to develop and implement training programs that would reinforce nursing students' competencies to care for older patients with dementia through consistent interactions and exchanges with field practitioners.

Purpose: This study aimed to describe and understand the meaning and nature of the process of forming a therapeutic relationship among nursing students working with older patients with dementia in long-term care hospitals. Methods: In-depth interviews were conducted with 10 nursing students from September to October 2024. We examined and described the collected data based on Colaizzi's phenomenological method. Results: Seventeen theme clusters and five categories were derived from the nursing students' experiences. The five categories were as follows: preparing for scheduled encounters with unfamiliar people, embarking upon exploration to build a relationship, making various efforts to maintain a therapeutic relationship, facing obstacles in maintaining a relationship, and witnessing myself growing in a therapeutic relationship. Conclusion Efforts should be made to develop and implement training programs that would reinforce nursing students' competencies to care for older patients with dementia through consistent interactions and exchanges with field practitioners.

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.