Background: and Purpose To determine the clinical phenotypes, relapse timing, treatment responses, and outcomes of children with relapsing myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD). Methods: We collected the demographic, clinical, laboratory, and radiological data of patients aged <18 years who had been diagnosed with MOGAD at Seoul National University Children’s Hospital between January 2010 and January 2022; 100 were identified as positive for MOG antibodies, 43 of whom experienced relapse. Results: The median age at onset was 7 years (range 2–16 years). The median number of relapses was 2 (range 1–8), and patients were followed up for a median of 65 months (range 5–214 months). The first relapse was experienced before 3 months from onset by 15 patients (34.9%). The most-common initial phenotypes were acute disseminated encephalomyelitis (n=17, 39.5%) and optic neuritis (ON; n=11, 25.6%). The most-common relapse phenotypes were neuromyelitis optica spectrum disorder (n=9, 20.9%), relapsing ON (n=6, 14.0%), and multiphasic disseminated encephalomyelitis (n=6, 14.0%). Many of the patients (n=18, 41.9%) were not specifically categorized. A high proportion of these patients had non-acute disseminated encephalomyelitis encephalitis. Atypical phenotypes such as prolonged fever or hemiplegic migraine-like episodes were also noted. Mycophenolate mofetil and cyclic immunoglobulin treatment significantly reduced the annual relapse rates. Conclusions Our 43 pediatric patients with relapsing MOGAD showed a tendency toward early relapse and various relapse phenotypes. The overall prognoses of these patients were good regardless of phenotype or response to second-line immunosuppressant treatment.

The peer review process ensures the integrity of scientific research. This is particularly important in the medical field, where research findings directly impact patient care. However, the rapid growth of publications has strained reviewers, causing delays and potential declines in quality. Generative artificial intelligence, especially large language models (LLMs) such as ChatGPT, may assist researchers with efficient, high-quality reviews. This review explores the integration of LLMs into peer review, highlighting their strengths in linguistic tasks and challenges in assessing scientific validity, particularly in clinical medicine. Key points for integration include initial screening, reviewer matching, feedback support, and language review. However, implementing LLMs for these purposes will necessitate addressing biases, privacy concerns, and data confidentiality. We recommend using LLMs as complementary tools under clear guidelines to support, not replace, human expertise in maintaining rigorous peer review standards.

Background: and Purpose To determine the clinical phenotypes, relapse timing, treatment responses, and outcomes of children with relapsing myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD). Methods: We collected the demographic, clinical, laboratory, and radiological data of patients aged <18 years who had been diagnosed with MOGAD at Seoul National University Children’s Hospital between January 2010 and January 2022; 100 were identified as positive for MOG antibodies, 43 of whom experienced relapse. Results: The median age at onset was 7 years (range 2–16 years). The median number of relapses was 2 (range 1–8), and patients were followed up for a median of 65 months (range 5–214 months). The first relapse was experienced before 3 months from onset by 15 patients (34.9%). The most-common initial phenotypes were acute disseminated encephalomyelitis (n=17, 39.5%) and optic neuritis (ON; n=11, 25.6%). The most-common relapse phenotypes were neuromyelitis optica spectrum disorder (n=9, 20.9%), relapsing ON (n=6, 14.0%), and multiphasic disseminated encephalomyelitis (n=6, 14.0%). Many of the patients (n=18, 41.9%) were not specifically categorized. A high proportion of these patients had non-acute disseminated encephalomyelitis encephalitis. Atypical phenotypes such as prolonged fever or hemiplegic migraine-like episodes were also noted. Mycophenolate mofetil and cyclic immunoglobulin treatment significantly reduced the annual relapse rates. Conclusions Our 43 pediatric patients with relapsing MOGAD showed a tendency toward early relapse and various relapse phenotypes. The overall prognoses of these patients were good regardless of phenotype or response to second-line immunosuppressant treatment.

The peer review process ensures the integrity of scientific research. This is particularly important in the medical field, where research findings directly impact patient care. However, the rapid growth of publications has strained reviewers, causing delays and potential declines in quality. Generative artificial intelligence, especially large language models (LLMs) such as ChatGPT, may assist researchers with efficient, high-quality reviews. This review explores the integration of LLMs into peer review, highlighting their strengths in linguistic tasks and challenges in assessing scientific validity, particularly in clinical medicine. Key points for integration include initial screening, reviewer matching, feedback support, and language review. However, implementing LLMs for these purposes will necessitate addressing biases, privacy concerns, and data confidentiality. We recommend using LLMs as complementary tools under clear guidelines to support, not replace, human expertise in maintaining rigorous peer review standards.

Background: and Purpose To determine the clinical phenotypes, relapse timing, treatment responses, and outcomes of children with relapsing myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD). Methods: We collected the demographic, clinical, laboratory, and radiological data of patients aged <18 years who had been diagnosed with MOGAD at Seoul National University Children’s Hospital between January 2010 and January 2022; 100 were identified as positive for MOG antibodies, 43 of whom experienced relapse. Results: The median age at onset was 7 years (range 2–16 years). The median number of relapses was 2 (range 1–8), and patients were followed up for a median of 65 months (range 5–214 months). The first relapse was experienced before 3 months from onset by 15 patients (34.9%). The most-common initial phenotypes were acute disseminated encephalomyelitis (n=17, 39.5%) and optic neuritis (ON; n=11, 25.6%). The most-common relapse phenotypes were neuromyelitis optica spectrum disorder (n=9, 20.9%), relapsing ON (n=6, 14.0%), and multiphasic disseminated encephalomyelitis (n=6, 14.0%). Many of the patients (n=18, 41.9%) were not specifically categorized. A high proportion of these patients had non-acute disseminated encephalomyelitis encephalitis. Atypical phenotypes such as prolonged fever or hemiplegic migraine-like episodes were also noted. Mycophenolate mofetil and cyclic immunoglobulin treatment significantly reduced the annual relapse rates. Conclusions Our 43 pediatric patients with relapsing MOGAD showed a tendency toward early relapse and various relapse phenotypes. The overall prognoses of these patients were good regardless of phenotype or response to second-line immunosuppressant treatment.

The peer review process ensures the integrity of scientific research. This is particularly important in the medical field, where research findings directly impact patient care. However, the rapid growth of publications has strained reviewers, causing delays and potential declines in quality. Generative artificial intelligence, especially large language models (LLMs) such as ChatGPT, may assist researchers with efficient, high-quality reviews. This review explores the integration of LLMs into peer review, highlighting their strengths in linguistic tasks and challenges in assessing scientific validity, particularly in clinical medicine. Key points for integration include initial screening, reviewer matching, feedback support, and language review. However, implementing LLMs for these purposes will necessitate addressing biases, privacy concerns, and data confidentiality. We recommend using LLMs as complementary tools under clear guidelines to support, not replace, human expertise in maintaining rigorous peer review standards.

Objectives: Since the enactment of the School Nutrition Act in 1981, school lunch programs in South Korea have grown quantitatively and qualitatively with a current student participation rate of 99.8%. Nonetheless, educational materials are needed to reduce misunderstanding and ignorance about school lunch programs. This study aimed to develop 3 educational videos that help students of various ages (kindergarteners/lower-grade elementary, upper-grade elementary, and secondary school, respectively), understand the school lunch program. Methods: A scenario was created, was made, and the opinions on the scenario from experts in foodservice sectors were collected. A survey was conducted to students and parents to determine topics they wanted to know about school foodservice. The final videos were produced using this information and the expert opinions. The data were analyzed using SPSS 27.0 for Mac (IBM Corp., Armonk, NY, USA); a P-value of < 0.05 was considered significant. Results: Three videos on school foodservice were developed for various age levels of students: kindergarten/lower-grade elementary, upper-grade elementary, and secondary school. Additionally, English subtitles were included for the multicultural student population. These videos, each lasting about 7 minutes, cover topics such as nutrition, hygiene, and the cultural significance of the school lunch program. The survey results showed that parents and students wanted to know the following topics about the school lunch program: “nutritionally balanced diet” (11.9%), “purchasing safe food ingredients” (10.9%), and “healthy eating habits” (9.9%). Conclusions The developed videos will serve as valuable educational resources on school foodservice, foster a deeper understanding of the school lunch program in parents and students, and potentially address their inquiries regarding production processes, nutrition, hygiene, cultural heritage, and health.

Objective: Suicide is a significant public health issue, with South Korea having the highest suicide rate among Organisation for Economic Cooperation and Development countries. This study aimed to develop clinical guidelines for suicide prevention in psychiatric patients in Korea using the ADAPTE methodology. Methods: The development process involved a comprehensive review of literature, expert consultations, and consensus-building using the Nominal Group Technique and Delphi method. The guidelines focus on evidence-based psychiatric treatments, including both pharmacological and non-pharmacological approaches, tailored to the Korean context. Key findings underscoring the need for standardized treatment protocols for patients with major psychiatric disorders, including bipolar disorder, major depressive disorder, and schizophrenia. Results: The guidelines incorporate treatments like lithium, clozapine, atypical antipsychotics, electroconvulsive therapy, and cognitive behavioral therapy, which have shown effectiveness in suicide prevention. Applicability and acceptability within Korea’s healthcare system were addressed, ensuring feasibility given the country’s medical insurance coverage and accessibility. The guidelines were validated through expert reviews and Delphi rounds, achieving consensus on the final recommendations. Conclusion The developed guidelines provide a structured, evidence-based approach to reducing suicide rates among psychiatric patients in Korea. Future research will focus on expanding these guidelines to include screening protocols for high-risk groups.

Rare endocrine diseases are complex conditions that require lifelong specialized care due to their chronic nature and associated long-term complications. In Korea, a lack of nationwide data on clinical practice and outcomes has limited progress in patient care. Therefore, the Multicenter Networks for Ideal Outcomes of Pediatric Rare Endocrine and Metabolic Disease (OUTSPREAD) study was initiated. This study involves 30 centers across Korea. The study aims to improve the long-term prognosis of Korean patients with rare endocrine diseases by collecting comprehensive clinical data, biospecimens, and patient-reported outcomes to identify complications and unmet needs in patient care. Patients with childhood-onset pituitary, adrenal, or gonadal disorders, such as craniopharyngioma, congenital adrenal hyperplasia (CAH), and Turner syndrome were prioritized. The planned enrollment is 1,300 patients during the first study phase (2022–2024). Clinical, biochemical, and imaging data from diagnosis, treatment, and follow-up during 1980–2023 were retrospectively reviewed. For patients who agreed to participate in the prospective cohort, clinical data and biospecimens will be prospectively collected to discover ideal biomarkers that predict the effectiveness of disease control measures and prognosis. Patient-reported outcomes, including quality of life and depression scales, will be evaluated to assess psychosocial outcomes. Additionally, a substudy on CAH patients will develop a steroid hormone profiling method using liquid chromatography-tandem mass spectrometry to improve diagnosis and monitoring of treatment outcomes. This study will address unmet clinical needs by discovering ideal biomarkers, introducing evidence-based treatment guidelines, and ultimately improving long-term outcomes in the areas of rare endocrine and metabolic diseases.

Objectives: This study examined the changes in the characteristics of high-risk suicide groups in South Korea before and after the COVID-19 pandemic using the Korean Cohort for the Model Predicting a Suicide and Suicide-related Behavior (K-COMPASS) cohort. Methods: The K-COMPASS is a longitudinal cohort study that started in 2015. The participants included suicide attempters and individuals with suicidal ideation from various hospitals and mental health centers in South Korea. This study compared the sociodemographic and psychiatric characteristics of 800 participants from the first cohort (2015–2019) with 511 participants from the second and third cohorts (2019–2024). Data were collected through structured interviews and validated scales. Results: The second and third cohort participants were younger, had a higher proportion of females, and exhibited more severe psychiatric symptoms and higher suicidal risk than the first cohort. The prevalence of physical illnesses decreased, while the use of psychiatric medications and the severity of mental health issues increased. In addition, significant sociodemographic changes were observed, such as higher educational levels and urban residency. Conclusion Significant shifts in the characteristics of high-risk suicide groups were observed during the COVID-19 pandemic, highlighting the need for targeted mental health interventions focusing on younger individuals and females to prevent suicide in high-risk groups.