Gastroesophageal reflux disease (GERD) is a chronic and relapsing gastrointestinal disorder characterized by the reflux of gastric contents into the esophagus, leading to troublesome symptoms and/or complications. Since the publication of the 2020 Seoul Consensus on GERD, significant new evidence has emerged, particularly regarding acid-suppressive therapies and diagnostic approaches. This 2025 focused update aims to refine GERD management strategies by incorporating the latest evidence on acid suppressive therapies and regional considerations in Asian populations. This study builds on the 2020 Seoul Consensus by integrating systematic reviews, meta-analyses, and expert consensuses to offer updated recommendations for the definition and medical treatment of GERD. These guidelines incorporate recent advances in acid-suppressive therapies, particularly potassium-competitive acid blockers, and adopt updated diagnostic frameworks in accordance with the Lyon Consensus 2.0. Key clinical questions were identified and structured using the following format: Population, Intervention, Comparator, Outcome. The resulting recommendations address the initial treatment, long-term maintenance strategies, and role of personalized therapy based on disease severity, such as the grade of reflux esophagitis. Six key statements are presented: updated definition and classification of GERD (Statement 1); initial and long-term treatment strategies tailored to GERD phenotypes, such as non-erosive reflux disease, mild erosive esophagitis, and severe erosive esophagitis (Statements 2-5); and dose optimization strategies for long-term safety (Statement 6). These guidelines aim to support gastroenterologists and general healthcare providers in making individualized evidence-based decisions for GERD management.

In forensic medicine, age estimation commonly involves assessing age-related changes in teeth and skeletal structures. Vertebral morphological alterations, such as osteophyte formation, serve as age indicators. Recent studies using deep-learning techniques, such as neural networks, for age estimation from radiographic images have been conducted, reporting significantly higher accuracy than previous studies. This study aimed to estimate age using neural network-based deep-learning techniques applied to computed tomography (CT) cross-sectional images of the spine and evaluate its feasibility. Postmortem CT scans of 214 cadavers with varying decomposition levels were used. Coronal and sagittal cross-sectional images penetrating the center of each vertebral body were extracted for the 11th and 12th thoracic vertebrae and the first to fifth lumbar vertebrae. Using these images, along with the chronological ages of deceased individuals, an age estimation model was developed through regression analysis in PyTorch, employing a convolutional neural networks architecture with five-fold cross-validation. The model achieved a mean absolute error of 5.385 years, root mean squared error of 7.029 years, and coefficient of determination of 0.793. Although the sample size was relatively small, the results suggested the potential applicability of vertebral imagingbased age estimation in the Korean population. Further research using a larger dataset may improve the accuracy and reliability of the model.

The sixth edition of the Korean Medication Algorithm Project for Depressive Disorder (KMAP-DD) was published in 2025. This review compared KMAP-DD 2025 with four major international clinical practice guidelines: Canadian Network for Mood and Anxiety Treatments Clinical Guidelines for the Management of Major Depressive Disorders, National Institute for Health and Care Excellence Depression Guideline, Royal Australian and New Zealand College of Psychiatrists Clinical Practice Guidelines for Mood Disorders, and British Association for Psychopharmacology Guideline. While KMAP-DD is based on expert consensus, and others on evidence-based methods, overall treatment strategies for depressive episodes were fairly consistent. Especially, KMAP-DD 2025 offers more structured recommendations in areas lacking strong evidence, such as premenstrual dysphoric disorder, perinatal depression, and depression with medical comorbidities. KMAP-DD 2025 also reflected Korean clinical practice patterns emphasizing rapid symptom relief and early use of combination strategies. Despite limitations as a consensus-based guideline, KMAP-DD 2025 complements evidence-based approaches and provides practical, situation-specific guidance for real-world clinical decision-making in Korea.

Objective: Objective of this study is to evaluate the association between high risk of depression and metabolic diseases such as hypertension, diabetes, and dyslipidemia in Korean cervical cancer patients. Methods: A total of 330 women with cervical cancer were included in this study, using data from the Korea National Health and Nutrition Examination Survey from 2010 to 2021. Participants were categorized into two groups—high risk of depression and non-depression—based on their answers to survey items related to depression. A multivariate logistic regression analysis was used to evaluate the influence of metabolic diseases on high risk of depression in patients with cervical cancer. Results: A total of 78 (23.64%) and 252 (76.36%) women were classified into the high risk of depression and non-depression groups, respectively. In multivariate logistic regression analysis adjusting for age, menopausal status, and smoking status, diabetes was associated with an odds ratio of 2.47 (95% confidence interval: 1.205, 5.071) for high risk of depression in cervical cancer patients. However, among the metabolic diseases, hypertension, and dyslipidemia were not associated with high risk of depression in patients with cervical cancer. Conclusion This study suggests that diabetes may be associated with a increased risk of high risk of depression in cervical cancer patients. Therefore, appropriate treatment of diabetes in cervical cancer patients may contribute to lowering the risk of depression in the future.

Objective: Objective of this study is to evaluate the association between high risk of depression and metabolic diseases such as hypertension, diabetes, and dyslipidemia in Korean cervical cancer patients. Methods: A total of 330 women with cervical cancer were included in this study, using data from the Korea National Health and Nutrition Examination Survey from 2010 to 2021. Participants were categorized into two groups—high risk of depression and non-depression—based on their answers to survey items related to depression. A multivariate logistic regression analysis was used to evaluate the influence of metabolic diseases on high risk of depression in patients with cervical cancer. Results: A total of 78 (23.64%) and 252 (76.36%) women were classified into the high risk of depression and non-depression groups, respectively. In multivariate logistic regression analysis adjusting for age, menopausal status, and smoking status, diabetes was associated with an odds ratio of 2.47 (95% confidence interval: 1.205, 5.071) for high risk of depression in cervical cancer patients. However, among the metabolic diseases, hypertension, and dyslipidemia were not associated with high risk of depression in patients with cervical cancer. Conclusion This study suggests that diabetes may be associated with a increased risk of high risk of depression in cervical cancer patients. Therefore, appropriate treatment of diabetes in cervical cancer patients may contribute to lowering the risk of depression in the future.

Objective: Objective of this study is to evaluate the association between high risk of depression and metabolic diseases such as hypertension, diabetes, and dyslipidemia in Korean cervical cancer patients. Methods: A total of 330 women with cervical cancer were included in this study, using data from the Korea National Health and Nutrition Examination Survey from 2010 to 2021. Participants were categorized into two groups—high risk of depression and non-depression—based on their answers to survey items related to depression. A multivariate logistic regression analysis was used to evaluate the influence of metabolic diseases on high risk of depression in patients with cervical cancer. Results: A total of 78 (23.64%) and 252 (76.36%) women were classified into the high risk of depression and non-depression groups, respectively. In multivariate logistic regression analysis adjusting for age, menopausal status, and smoking status, diabetes was associated with an odds ratio of 2.47 (95% confidence interval: 1.205, 5.071) for high risk of depression in cervical cancer patients. However, among the metabolic diseases, hypertension, and dyslipidemia were not associated with high risk of depression in patients with cervical cancer. Conclusion This study suggests that diabetes may be associated with a increased risk of high risk of depression in cervical cancer patients. Therefore, appropriate treatment of diabetes in cervical cancer patients may contribute to lowering the risk of depression in the future.

Objective: Objective of this study is to evaluate the association between high risk of depression and metabolic diseases such as hypertension, diabetes, and dyslipidemia in Korean cervical cancer patients. Methods: A total of 330 women with cervical cancer were included in this study, using data from the Korea National Health and Nutrition Examination Survey from 2010 to 2021. Participants were categorized into two groups—high risk of depression and non-depression—based on their answers to survey items related to depression. A multivariate logistic regression analysis was used to evaluate the influence of metabolic diseases on high risk of depression in patients with cervical cancer. Results: A total of 78 (23.64%) and 252 (76.36%) women were classified into the high risk of depression and non-depression groups, respectively. In multivariate logistic regression analysis adjusting for age, menopausal status, and smoking status, diabetes was associated with an odds ratio of 2.47 (95% confidence interval: 1.205, 5.071) for high risk of depression in cervical cancer patients. However, among the metabolic diseases, hypertension, and dyslipidemia were not associated with high risk of depression in patients with cervical cancer. Conclusion This study suggests that diabetes may be associated with a increased risk of high risk of depression in cervical cancer patients. Therefore, appropriate treatment of diabetes in cervical cancer patients may contribute to lowering the risk of depression in the future.

Objective: Objective of this study is to evaluate the association between high risk of depression and metabolic diseases such as hypertension, diabetes, and dyslipidemia in Korean cervical cancer patients. Methods: A total of 330 women with cervical cancer were included in this study, using data from the Korea National Health and Nutrition Examination Survey from 2010 to 2021. Participants were categorized into two groups—high risk of depression and non-depression—based on their answers to survey items related to depression. A multivariate logistic regression analysis was used to evaluate the influence of metabolic diseases on high risk of depression in patients with cervical cancer. Results: A total of 78 (23.64%) and 252 (76.36%) women were classified into the high risk of depression and non-depression groups, respectively. In multivariate logistic regression analysis adjusting for age, menopausal status, and smoking status, diabetes was associated with an odds ratio of 2.47 (95% confidence interval: 1.205, 5.071) for high risk of depression in cervical cancer patients. However, among the metabolic diseases, hypertension, and dyslipidemia were not associated with high risk of depression in patients with cervical cancer. Conclusion This study suggests that diabetes may be associated with a increased risk of high risk of depression in cervical cancer patients. Therefore, appropriate treatment of diabetes in cervical cancer patients may contribute to lowering the risk of depression in the future.

Objective: Since its development in 2002 by the Korean College of Neuropsychopharmacology and the Korean Society for Affective Disorders, the Korean Medication Algorithm Project for Depressive Disorder (KMAP-DD) has undergone five revisions. Methods: To improve survey efficiency, reflect general clinical practice, and facilitate comparisons with previous KMAP-DD revisions, the overall structure of the questionnaire was retained. The six sections of the questionnaire were as follows:1) pharmacological treatment strategies for major depressive disorder with and without psychotic features; 2) pharmacological treatment strategies for persistent depressive disorder and other depressive disorder subtypes; 3) consensus on treatment-resistant depression; 4) selection of an antidepressant in consideration of safety, adverse effects, and comorbid physical conditions; 5) treatment strategies for special populations (children/adolescents, elderly, and women); and 6) non-pharmacological biological therapies. First-, second-, and third-line treatment recommendations were statistically derived. Results: Compared to KMAP-DD 2021, only minor changes were noted, due to the limited introduction of new medications or treatment modalities. Nonetheless, notable shifts included an increased preference for atypical antipsychotics (AAPs), and higher preference of combination strategies involving AAPs and mood stabilizers, indicating a more proactive and intensive treatment trend in Korea. Conclusion KMAP-DD is expected to serve as a valuable clinical resource by providing expert consensus-based recommendations on specific treatment strategies and pharmacological options for major depressive disorders, thereby supporting the integration of real-world clinical practice with evidence-based medicine.

We analyzed the manner and cause of death in 1,193 forensic autopsies from the Jungbu province (central part of South Korea) conducted by the National Forensic Service Daejeon Institute in 2022. Analysis of the manner of deaths revealed that 43.1% (514/1,193 cases) were natural deaths; 42.8% (511/1,193 cases) were unnatural deaths; and 14.1% (168/1,193 cases) were unknown. Among the unnatural deaths, the major manner of death was 44.6% (228/511 cases) by accidents, 34.1% (174/511 cases) by suicide, 13.5% (69/511 cases) undetermined, and 7.8% (40/511 cases) by homicide. Among the unnatural deaths, the major causes of death was 38.4% (196/511 cases) by trauma, 20.4% (104/511 cases) by poisoning, and 17.6% (90/511 cases) by asphyxia. Falling was the major cause of death by trauma (58.7%, 115/196 cases), and strangulation was the major cause of death by asphyxia (75.6%, 68/90 cases). Among the natural deaths, heart disease was the major cause (46.7%, 240/514 cases), followed by endocrine, nutritional and metabolic diseases (14.0%, 72/514 cases). A time-series statistical analysis and comparison of the manner and cause of deaths in this province may facilitate more advanced interpretations relating to both public safety and healthcare in the future.