Background: and Purpose Treatments for neuromyelitis optica spectrum disorder (NMOSD) such as eculizumab, ravulizumab, satralizumab, and inebilizumab have significantly advanced relapse prevention, but they remain expensive. Rituximab is an off-label yet popular alternative that offers a cost-effective solution, but its real-world efficacy needs better quantification for guiding the application of newer approved NMOSD treatments (ANTs). This study aimed to determine real-world rituximab failure rates to anticipate the demand for ANTs and aid in resource allocation. Methods: We conducted a nationwide retrospective study involving 605 aquaporin-4-antibody-positive NMOSD patients from 22 centers in South Korea that assessed the efficacy and safety of rituximab over a median follow-up of 47 months. Results: The 605 patients treated with rituximab included 525 (87%) who received continuous therapy throughout the follow-up period (median=47 months, interquartile range=15–87 months). During this period, 117 patients (19%) experienced at least 1 relapse. Notably, 68 of these patients (11% of the total cohort) experienced multiple relapses or at least 1 severe relapse.Additionally, 2% of the patients discontinued rituximab due to adverse events, which included severe infusion reactions, neutropenia, and infections. Conclusions This study has confirmed the efficacy of rituximab in treating NMOSD, as evidenced by an 87% continuation rate among patients over a 4-year follow-up period. Nevertheless, the occurrence of at least one relapse in 19% of the cohort, including 11% who experienced multiple or severe relapses, and a 2% discontinuation rate due to adverse events highlight the urgent need for alternative therapeutic options.

Purpose: Pulmonary tumor thrombotic microangiopathy (PTTM) is a fatal complication of gastric cancer (GC). This study aimed to evaluate the clinical characteristics, outcomes, and immunohistochemical profiles of patients with GC-induced PTTM. Materials and Methods: From 2011 to 2023, 8 patients were clinically diagnosed with PTTM associated with GC antemortem. Clinical features and outcomes were reviewed, and immunohistochemical staining for c-erbB-2, MutL protein homolog 1, and programmed cell death ligand-1 was performed. Results: The median patient age was 56 years (range, 34–66 years). In all the patients, the tumors exhibited either ulceroinfiltrative or diffusely infiltrative gross morphology.The median tumor size was 5.8 cm (range, 2.0 cm–15.0 cm). Poorly differentiated adenocarcinoma was the most common histological type (6/8, 75%), followed by signet ring cell carcinoma (1/8, 12.5%) and moderately differentiated adenocarcinoma (1/8, 12.5%).Chest computed tomography revealed ground-glass opacities (7/8, 87.5%) or tree-in-bud signs (2/8, 25.0%) without definite evidence of pulmonary thromboembolism. Disseminated intravascular coagulation was present in 62.5% (5/8) of the patients diagnosed with PTTM.C-erbB-2 was positive in one patient (1/8, 12.5%). One patient who received palliative chemotherapy after developing PTTM survived for 35 days, whereas the other 7 patients who did not receive chemotherapy after developing PTTM survived for 7 days or less after PTTM diagnosis. Conclusions Most patients with GC-induced PTTM had an undifferentiated-type histology, infiltrative morphology, and extremely poor survival. Palliative chemotherapy may benefit patients with GC-induced PTTM; however, further studies are needed to explore the potential of targeted therapy in these patients.

Purpose: Since 1995, the Korean Gastric Cancer Association (KGCA) has been periodically conducting nationwide surveys on patients with surgically treated gastric cancer. This study details the results of the survey conducted in 2023. Materials and Methods: The survey was conducted from March to December 2024 using a standardized case report form. Data were collected on 86 items, including patient demographics, tumor characteristics, surgical procedures, and surgical outcomes. The results of the 2023 survey were compared with those of previous surveys. Results: Data from 12,751 cases were collected from 66 institutions. The mean patient age was 64.6 years, and the proportion of patients aged ≥71 years increased from 9.1% in 1995 to 31.7% in 2023. The proportion of upper-third tumors slightly decreased to 16.8% compared to 20.9% in 2019. Early gastric cancer accounted for 63.1% of cases in 2023.Regarding operative procedures, a totally laparoscopic approach was most frequently applied (63.2%) in 2023, while robotic gastrectomy steadily increased to 9.5% from 2.1% in 2014.The most common anastomotic method was the Billroth II procedure (48.8%) after distal gastrectomy and double-tract reconstruction (51.9%) after proximal gastrectomy in 2023.However, the proportion of esophago-gastrostomy with anti-reflux procedures increased to 30.9%. The rates of post-operative mortality and overall complications were 1.0% and 15.3%, respectively. Conclusions The results of the 2023 nationwide survey demonstrate the current status of gastric cancer treatment in Korea. This information will provide a basis for future gastric cancer research.

Gastric cancer is one of the most common cancers in both Korea and worldwide. Since 2004, the Korean Practice Guidelines for Gastric Cancer have been regularly updated, with the 4th edition published in 2022. The 4th edition was the result of a collaborative work by an interdisciplinary team, including experts in gastric surgery, gastroenterology, endoscopy, medical oncology, abdominal radiology, pathology, nuclear medicine, radiation oncology, and guideline development methodology. The current guideline is the 5th version, an updated version of the 4th edition. In this guideline, 6 key questions (KQs) were updated or proposed after a collaborative review by the working group, and 7 statements were developed, or revised, or discussed based on a systematic review using the MEDLINE, Embase, Cochrane Library, and KoreaMed database. Over the past 2 years, there have been significant changes in systemic treatment, leading to major updates and revisions focused on this area.Additionally, minor modifications have been made in other sections, incorporating recent research findings. The level of evidence and grading of recommendations were categorized according to the Grading of Recommendations, Assessment, Development and Evaluation system. Key factors for recommendation included the level of evidence, benefit, harm, and clinical applicability. The working group reviewed and discussed the recommendations to reach a consensus. The structure of this guideline remains similar to the 2022 version.Earlier sections cover general considerations, such as screening, diagnosis, and staging of endoscopy, pathology, radiology, and nuclear medicine. In the latter sections, statements are provided for each KQ based on clinical evidence, with flowcharts supporting these statements through meta-analysis and references. This multidisciplinary, evidence-based gastric cancer guideline aims to support clinicians in providing optimal care for gastric cancer patients.

Purpose: This study aimed to evaluate the performance of a clinical ladder system in a tertiary hospital by examining how nurses' clinical competence and perceptions of the system affect organizational commitment. Methods: The study involved 394 nurses working at a tertiary hospital. Data were collected from May 3 to July 10, 2023, using a self-reported questionnaire. Statistical analyses, including descriptive statistics, independent t-tests, one-way ANOVA, Kruskal-Wallis test, Scheffé post-hoc test, Pearson correlation, and hierarchical regression analysis, were performed using SPSS 27.0. Results: Nurses who applied for promotion to the CN III level and current CN III nurses reported higher clinical competence, perceptions of the clinical ladder system, and organizational commitment than those who did not and those at lower levels (p<.001). A positive correlation existed among all independent variables.Controlling for general characteristics, the effects of clinical competence and perceptions of the clinical ladder system explained 49% of organizational commitment variance (Adjusted R 2 =.49, F=33.43, p<.001). Conclusion Greater clinical competence and positive perceptions of the clinical ladder system are likely to enhance organizational commitment, emphasizing its effectiveness in fostering better organizational outcomes.

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.

Objective: To test the performance of an artificial intelligence-based computer-aided diagnosis (AI-CAD) designed for fullfield digital mammography (FFDM) when applied to synthetic mammography (SM). Materials and Methods: We analyzed 501 women (mean age, 57 ± 11 years) who underwent preoperative mammography and breast cancer surgery. This cohort consisted of 1002 breasts, comprising 517 with cancer and 485 without. All patients underwent digital breast tomosynthesis (DBT) and FFDM during the preoperative workup. The SM is routinely reconstructed using DBT. Commercial AI-CAD (Lunit Insight MMG, version 1.1.7.2) was retrospectively applied to SM and FFDM to calculate the abnormality scores for each breast. The median abnormality scores were compared for the 517 breasts with cancer using the Wilcoxon signed-rank test. Calibration curves of abnormality scores were evaluated. The discrimination performance was analyzed using the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity using a 10% preset threshold. Sensitivity and specificity were further analyzed according to the mammographic and pathological characteristics.The results of SM and FFDM were compared. Results: AI-CAD demonstrated a significantly lower median abnormality score (71% vs. 96%, P < 0.001) and poorer calibration performance for SM than for FFDM. SM exhibited lower sensitivity (76.2% vs. 82.8%, P < 0.001), higher specificity (95.5% vs.91.8%, P < 0.001), and comparable AUC (0.86 vs. 0.87, P = 0.127) than FFDM. SM showed lower sensitivity than FFDM in asymptomatic breasts, dense breasts, ductal carcinoma in situ, T1, N0, and hormone receptor-positive/human epidermal growth factor receptor 2-negative cancers but showed higher specificity in non-cancerous dense breasts. Conclusion AI-CAD showed lower abnormality scores and reduced calibration performance for SM than for FFDM.Furthermore, the 10% preset threshold resulted in different discrimination performances for the SM. Given these limitations, off-label application of the current AI-CAD to SM should be avoided.

Objective: In South Korea, there is a significant gap in systematic, evidence-based research on intensive case management (ICM) for individuals with severe mental illness (SMI). This study aims to evaluate the effectiveness of ICM through a randomized controlled trial (RCT) comparing ICM with standard case management (non-ICM). Methods: An RCT was conducted to assess the effectiveness of Seoul-intensive case management (S-ICM) vs. non-ICM in individuals with SMI in Seoul. A total of 78 participants were randomly assigned to either the S-ICM group (n=41) or the control group (n=37). Various clinical assessments, including the Brief Psychiatric Rating Scale (BPRS), Montgomery–Åsberg Depression Rating Scale, Health of the Nation Outcome Scale, and Clinical Global Impression-Improvement (CGI-I), along with quality-of-life measures such as the WHO Disability Assessment Schedule, WHO Quality of Life scale, and Multidimensional Scale of Perceived Social Support (MSPSS) were evaluated over a 3-month period. Statistical analyses, including analysis of covariance and logistic regression, were used to determine the effectiveness of S-ICM. Results: The S-ICM group had significantly lower odds of self-harm or suicidal attempts compared to the control group (adjusted odds ratio [aOR]=0.30, 95% confidence interval [CI]: 0.21–1.38). Psychiatric symptoms measured by the BPRS and perceived social support measured by the MSPSS significantly improved in the S-ICM group. The S-ICM group also had significantly higher odds of CGI-I compared to the control group (aOR=8.20, 95% CI: 2.66–25.32). Conclusion This study provides inaugural evidence on the effectiveness of S-ICM services, supporting their standardization and potential nationwide expansion.

Shoulder diseases pose a significant health challenge for older adults, often causing pain, functional decline, and decreased independence. This narrative review explores how deep learning (DL) can address diagnostic challenges by automating tasks such as image segmentation, disease detection, and motion analysis. Recent research highlights the effectiveness of DL-based convolutional neural networks and machine learning frameworks in diagnosing various shoulder pathologies. Automated image analysis facilitates the accurate assessment of rotator cuff tear size, muscle degeneration, and fatty infiltration in MRI or CT scans, frequently matching or surpassing the accuracy of human experts. Convolutional neural network-based systems are also adept at classifying fractures and joint conditions, enabling the rapid identification of common causes of shoulder pain from plain radiographs. Furthermore, advanced techniques like pose estimation provide precise measurements of the shoulder joint's range of motion and support personalized rehabilitation plans. These automated approaches have also been successful in quantifying local osteoporosis, utilizing machine learning-derived indices to classify bone density status. DL has demonstrated significant potential to improve diagnostic accuracy, efficiency, and consistency in the management of shoulder diseases in older patients. Machine learning-based assessments of imaging data and motion parameters can help clinicians optimize treatment plans and improve patient outcomes. However, to ensure their generalizability, reproducibility, and effective integration into routine clinical workflows, large-scale, prospective validation studies are necessary. As data availability and computational resources increase, the ongoing development of DL-driven applications is expected to further advance and personalize musculoskeletal care, benefiting both healthcare providers and the aging population.