Purpose: This study explores the experiences of practitioners involved in the Community Integrated Care for Individuals with Mental Illness pilot project in A City. The project integrates healthcare, housing, rehabilitation, and welfare services to support community integration and prevent rehospitalization. Methods: A qualitative descriptive study was conducted using focus group interviews with 12 practitioners with at least six months of experience in the project. Data was analyzed using content analysis based on Downe-Wamboldt's framework. Results: Four themes emerged: (1) Integration and Maintenance, (2) Change and Advancement, (3) Communication and Connection, and (4) Need and Challenge. The project improved service continuity, enhanced multidisciplinary collaboration, and increased professional efficacy. However, challenges such as resource limitations, policy constraints, and workforce shortages were identified. Conclusion The pilot project effectively supports mental health recovery and community integration. To ensure sustainability, service expansion, policy reinforcement, and workforce development are needed. Strengthening inter-agency collaboration and public awareness will further promote community-based mental health 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.

Purpose: To evaluate the compatibility and usability of test results obtained from the IDRA and Keratograph 5M in clinical settings by comparing their performance in patients with dry eye disease. Methods: From December 27 to 30, 2022, a study was conducted on 30 patients diagnosed with dry eye utilizing both the Keratograph 5M and IDRA devices. The parameters compared and analyzed included lipid layer thickness, tear meniscus height, tear film break-up time, and meibography. A paired t-test was used for statistical comparison. The lipid layer thickness in the Keratograph 5M was graded on a scale from 0 to 4 based on thickness. Results: No significant differences were found between the two devices in tear film break-up time, tear meniscus height, and meibography (p = 0.148, 0.072, 0.124, respectively). However, the tear lipid layer thickness measured by IDRA showed a proportional relationship with the grade assigned by the Keratograph 5M (Kendall R = 0.217, p = 0.037; Spearman R = 0.260, p = 0.045). Conclusions The IDRA device offers the advantage of performing multiple dry eye tests; simultaneously, thereby saving time compared to the Keratograph 5M. Both devices can be used compatibly with IDRA particularly advantageous for providing a numerical value for tear lipid layer thickness which enhances the convenience of dry eye diagnosis and treatment.

Systemic corticosteroids play an essential role in the management of asthma. During acute exacerbation, the short-term use of systemic corticosteroids is recommended. For patients with uncontrolled asthma and severe asthma, long-term and low-dose oral corticosteroids (OCS) have frequently been advocated. However, both short-term and long-term use of systemic corticosteroids carry the risk of adverse events (AEs), including various morbidities and even mortality. Despite recent progress in adult severe asthma management and the availability of new treatment options, the current domestic guidelines for asthma do not provide specific recommendations for oral corticosteroid tapering in patients with severe asthma. Therefore, the task force team of the severe asthma working group in the Korean Academy of Allergy, Asthma, and Clinical Immunology has proposed a tapering protocol for systemic corticosteroid use in severe asthma. This includes practical recommendations for monitoring OCS-related AE, particularly for adrenal insufficiency and osteoporosis, which suggests corticosteroid-sparing strategies that include alternative therapies, modifying treatable traits, timely specialist assessment, and shared decision-making with patients. However, further real-world research and collaboration with doctors from primary and academic institutes, patients, and policymakers are necessary to establish an OCS stewardship approach. This should include realistic OCS-tapering strategies for patients with severe asthma using regular OCS, education, and campaigns for patients, the public, and healthcare providers about the burden of severe asthma, as well as improving timely access to specialized severe asthma services for optimal management.

Purpose: This study explores the experiences of practitioners involved in the Community Integrated Care for Individuals with Mental Illness pilot project in A City. The project integrates healthcare, housing, rehabilitation, and welfare services to support community integration and prevent rehospitalization. Methods: A qualitative descriptive study was conducted using focus group interviews with 12 practitioners with at least six months of experience in the project. Data was analyzed using content analysis based on Downe-Wamboldt's framework. Results: Four themes emerged: (1) Integration and Maintenance, (2) Change and Advancement, (3) Communication and Connection, and (4) Need and Challenge. The project improved service continuity, enhanced multidisciplinary collaboration, and increased professional efficacy. However, challenges such as resource limitations, policy constraints, and workforce shortages were identified. Conclusion The pilot project effectively supports mental health recovery and community integration. To ensure sustainability, service expansion, policy reinforcement, and workforce development are needed. Strengthening inter-agency collaboration and public awareness will further promote community-based mental health 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.

Endometriosis, a prevalent but debilitating condition affecting women, poses significant challenges in diagnosis and management. The current 2024 guideline, developed by the Korean Society of Endometriosis (KSE), builds upon the 2018 KSE guideline. This guideline aims to provide customized recommendations tailored to Korea’s unique clinical aspects and medical environment, and addresses key areas such as diagnosis, medical and surgical management, considerations for special populations, and its complex relationship with cancer.

Purpose: This study aimed to present a novel method for estimating the effective atomic number(Zeff ) using dual-energy computed tomography (DECT) designed to improve accuracy andstreamline clinical workflows by reducing computational complexity. Methods: The proposed model leverages the DECT-derived mass attenuation coefficients without detailed compositional analysis. By incorporating additional parameters into the conventional Rutherford model, such as exponential and trigonometric functions, the model effectively capturescomplex variations in attenuation, enabling precise Zeff estimation. Model fitting was performedusing dual-energy data and evaluated using the percentage difference in error rates. Results: Compared with the Rutherford model, which recorded a maximum error rate of 0.55%, the proposed model demonstrated a significantly lower maximum error rate of 0.15%, highlightingits precision. Zeff estimates for various materials closely matched the reference values, confirmingthe improved accuracy of the model. Conclusions The proposed DECT-based model provides a practical and efficient approach to Zeff estimation, with potential applications in radiation oncology, particularly for accurate stopping power ratio calculations in proton and heavy ion therapies.

Endometriosis, a prevalent but debilitating condition affecting women, poses significant challenges in diagnosis and management. The current 2024 guideline, developed by the Korean Society of Endometriosis (KSE), builds upon the 2018 KSE guideline. This guideline aims to provide customized recommendations tailored to Korea’s unique clinical aspects and medical environment, and addresses key areas such as diagnosis, medical and surgical management, considerations for special populations, and its complex relationship with cancer.

Purpose: This study aimed to present a novel method for estimating the effective atomic number(Zeff ) using dual-energy computed tomography (DECT) designed to improve accuracy andstreamline clinical workflows by reducing computational complexity. Methods: The proposed model leverages the DECT-derived mass attenuation coefficients without detailed compositional analysis. By incorporating additional parameters into the conventional Rutherford model, such as exponential and trigonometric functions, the model effectively capturescomplex variations in attenuation, enabling precise Zeff estimation. Model fitting was performedusing dual-energy data and evaluated using the percentage difference in error rates. Results: Compared with the Rutherford model, which recorded a maximum error rate of 0.55%, the proposed model demonstrated a significantly lower maximum error rate of 0.15%, highlightingits precision. Zeff estimates for various materials closely matched the reference values, confirmingthe improved accuracy of the model. Conclusions The proposed DECT-based model provides a practical and efficient approach to Zeff estimation, with potential applications in radiation oncology, particularly for accurate stopping power ratio calculations in proton and heavy ion therapies.