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.

In patients with differentiated thyroid cancer (DTC), initial recurrence risk stratification based on clinical, histopathological, and perioperative data remains the key determinant for guiding management strategies during the first 1-2 years post-treatment. However, the adoption of ongoing risk stratification (ORS), which dynamically reassesses risk by integrating longitudinal clinical data and treatment response, enables more precise long-term prognostic assessment and facilitates highly individualized management. Building upon recent guidelines, the 2026 KTA guideline has been further refined by incorporating robust evidence from large-scale national cohorts and comprehensive systematic reviews. These updated recommendations outline contemporary concepts of ORS, risk-adapted TSH suppression targets, optimized surveillance modalities for recurrence detection, and disease-specific long-term follow-up strategies. Reflecting the paradigm shift toward de-escalated treatment, this revision integrates evolved perspectives on TSH suppression intensity, the clinical interpretation of thyroglobulin levels, and tailored follow-up intervals. These evidence-based recommendations aim to minimize unnecessary treatment and excessive surveillance in the large proportion of patients with excellent prognosis after initial therapy, while ensuring that each patient receives appropriately tailored and effective long-term management.

Background: Left bundle branch block (LBBB) significantly increases the risk of left ventricular systolic dysfunction (LVSD) due to cardiac dyssynchrony. Although artificial intelligence–enabled electrocardiography (AI-ECG) mod‑ els show promise in detecting LVSD, their performance in LBBB patients remains underexplored. We hypothesized that an AI-ECG model clinically validated for detecting LVSD would accurately detect LVSD and predict future clinical outcomes in LBBB patients. Methods: In this retrospective multicenter study, 5,689 expert-validated LBBB ECGs collected from 2,813 patients between 2016 and 2024 were analyzed using a previously developed and validated AI-ECG model. LVSD was defined as an ejection fraction of ≤ 40%. Model performance was assessed using the area under the receiver operating char‑ acteristic curve (AUROC), the area under the precision-recall curve (AUPRC), sensitivity, and specificity. Patients were stratified into high- and low-risk groups based on a threshold that achieved 90% sensitivity. A Kaplan–Meier analysis was used to compare clinical outcomes. Results: Among the 2,813 LBBB patients (mean age, 70.7 years; male sex, 43.7%), hypertension and a history of heart failure were common. The AiTiALVSD model showed strong diagnostic performance for LVSD (AUROC, 0.930 [95% CI, 0.924–0.937]; AUPRC, 0.913 [95% CI, 0.902–0.923]; sensitivity, 0.979; specificity, 0.473). During the mean follow-up of 4.1 years, high-risk patients had significantly higher hazards than low-risk patients for all-cause mortality (adjusted hazard ratio [HR], 1.87; 95% CI, 1.53–2.28), implantable cardioverter defibrillator/cardiac resynchronization therapy implantation (adjusted HR, 15.2; 95% CI, 7.51–30.77), and cardiovascular hospitalization (adjusted HR, 1.11; 95% CI, 0.96–1.28). Conclusions AiTiALVSD effectively detects LVSD and stratifies long-term cardiovascular risk in LBBB patients, support‑ ing its clinical utility for early detection and patient management.

Abrupt vessel closure (AVC) is a complication of percutaneous coronary intervention (PCI) and is defined as the sudden cessation of forward coronary blood flow due to a variety of mechanisms. The incidence of AVC has markedly decreased from approximately 3.0% in the early era to about 0.3% today. Nevertheless, cardiovascular interventionists must remain prepared to manage AVC effectively, given its significant impact on clinical outcomes.AVC can arise from several mechanisms, including dissection, intramural hematoma, intracoronary thrombosis, air embolism, vasospasm, and no-reflow. The clinical impact of AVC varies depending on the extent of myocardium affected, ranging from asymptomatic events or transient ischemic chest pain to cardiogenic shock or cardiac arrest. Both a general approach for stabilizing hemodynamic consequences and an etiology-specific management strategy are essential. Hasty decision-making may worsen the situation, whereas a structured approach—focused on hemodynamic stabilization, logical diagnostic processes, and targeted interventions—can improve outcomes. In this narrative review, we describe the mechanisms underlying each etiology, outline mechanism-specific management strategies, and discuss general approaches to managing patients with AVC through logical diagnostic and treatment processes. We hope this review offers valuable insights into this uncommon but significant complication and enhances readers’ skills in managing AVC more effectively during PCI.

The coronavirus disease 2019 (COVID-19) pandemic has substantially influenced nursing environments and has underscored the importance of active patient care. Nursing intention plays a critical role in the provision of care for patients with COVID-19; however, limited evidence exists regarding the factors that influence nurses’ intention to provide patient care specific to COVID-19. This study aimed to examine factors associated with nursing intention for COVID-19 patient care, guided by the Theory of Planned Behavior. Methods: This study employed a cross-sectional descriptive design. Data were collected from August 30 to October 1, 2020, using structured questionnaires completed by 169 clinical nurses working in hospitals with more than 600 beds in Seoul, Korea. The collected data were analyzed using multiple regression analysis. Results: Behavioral beliefs (β=.34, p<.001) and perceived behavioral control (β=.24, p<.001) were significantly associated with nursing intention for COVID-19 patient care. Conclusion: There is a need to develop specific strategies and educational programs to enhance nursing intention for COVID-19 patient care in the context of emerging infectious diseases by strengthening behavioral beliefs and perceived behavioral control. Providing up-to-date care protocols or simulation-based education may help increase nurses’ behavioral beliefs and perceived behavioral control.

Vaccines are highly effective, but rare or delayed adverse events following immunization (AEFIs) require post-licensure surveillance beyond clinical trials. Korea lacks a comprehensive, active, database-based framework, yet key assets exist: nationwide claims databases (National Health Insurance Service/Health Insurance Review and Assessment Service), the national immunization registry (Korea Disease Control and Prevention Agency’s Immunization Registry Information System) for National Immunization Program (NIP) and non-NIP vaccines, and increasingly standardized hospital electronic health records.We propose a federated, code to data architecture with data linkages between these data.Implementation should adopt a common data model (CDM), standardized case definitions, latency accounting, and transparent public reporting under strong privacy governance. Major challenges include multi step administrative approvals for data linkage, incomplete capture of adult non-NIP vaccinations, heterogeneous hospital data structures, and strict data protection constraints. Strategic priorities are to streamline statutory and administrative processes for public health use, mandate or enable claims-based capture of adult vaccinations, enhance CDM based interoperability, and develop secure hubs for aggregated outputs. With these measures, Korea will be well positioned to establish a scalable active surveillance system capable of detecting rare AEFIs, supporting transparent and evidence-based communication, and ensuring equitable injury compensation grounded in domestic data.

Background: The incidence of preterm birth in Korea increased from 6.5% in 2013 to 9.7% in 2020. Very low birth weight (VLBW) infants, defined as those weighing < 1,500 g, are particularly vulnerable to numerous health risks. Breast milk provision reduces the incidence of complications in this vulnerable population. The objective of this study was to examine the rate and factors associated with breast milk provision at neonatal intensive care unit (NICU) discharge and to investigate its potential effects on growth and developmental outcomes at 18–24 months corrected age (CA). Methods: We conducted this cohort study using data from over 70 NICUs participating in the Korean Neonatal Network. VLBW infants born between January 2019 and December 2020 at a gestational age of 23 +0 to 31 +6 weeks were included. Discharge feeding types were analyzed of 2,490 infants, while follow-up assessments of growth and neurodevelopmental outcomes at 18–24 months of CA were available for 1,426 infants. Propensity score matching was used for comparative analysis. Results: The rate of breast milk provision at discharge among VLBW infants was 55.9% in 2019 and 56.5% in 2020. Factors that were positively associated with breast milk feeding included higher maternal education level and antenatal steroid use. In contrast, maternal hypertensive disorders, cesarean section, and severe neonatal morbidities (e.g., necrotizing enterocolitis) were correlated with lower breast milk feeding rates at the time of discharge.The provision of breast milk at discharge was not associated with a higher risk of suboptimal growth (below two standard deviations) compared to control infants at 18–24 months of CA. Neurodevelopmental assessments indicated that breast milk was associated with a reduced risk of developmental delay (adjusted odds ratio, 0.72; 95% confidence interval, 0.56–0.94) at follow-up. Conclusion Breast milk provision to VLBW infants at NICU discharge in Korea was comparable to that in other countries. This nationwide study highlights the critical role of breast milk in promoting the neurodevelopment of VLBW infants. Future efforts should focus on identifying the barriers to breast milk provision to improve health outcomes in vulnerable populations.

Purpose: This study evaluated the clinical outcomes and prognostic factors in patients with borderline resectable pancreatic cancer (BRPC) and locally advanced pancreatic cancer (LAPC) treated with upfront FOLFIRINOX followed by local-regional therapy (LRT), surgical resection (SR), and radiotherapy (RT). We aimed to identify specific patient subgroups for which RT may serve as a reasonable alternative to SR for local tumor control. Methods: We retrospectively analyzed 116 patients (SR group, n= 70; RT group, n= 46) at a single center between 2015 and 2020. Survival outcomes were compared based on LRT modalities, focusing on identifying subgroups in which RT provided an efficacy comparable to that of SR. Results: Among 116 patients, the SR group achieved a significantly higher 5-year overall survival (OS) than the RT group (27.1% vs. 8.7%, P< 0.0001), despite similar progression-free survival (P= 0.23). Significant prognostic factors for OS included carbohydrate antigen 19-9 (CA19-9) response in BRPC (P= 0.02) and radiologic partial response in LAPC (P= 0.05). Subgroup analysis revealed that, while SR provided a survival advantage in CA19-9 responders, no significant difference in OS was observed between SR and RT in CA19-9 non-responders (P= 0.37). Conclusion Although surgery remains the gold standard, RT may be considered a justifiable local alternative for CA19-9 non-responders and surgically ineligible patients with LAPC, yielding comparable outcomes in these specific, biologically unfavorable subgroups.

Background: Workers are commonly exposed to diesel engine exhaust (DEE) from diesel-powered engines and vehicles (DEVs), which contain harmful particulates such as black carbon (BC). This study aimed to characterize the peak BC exposures of workers operating or working near DEVs. Methods: BC levels were recorded every minute from workers driving or working near DEVs using a portable aethalometer and were categorized by job type and activity. Peak BC levels were characterized using the occupational exposure limits for DEE (measured as elemental carbon) of 10 μg/m 3 and 50 μg/ m3 as cut-off values. Results: Forklift operators, garbage collectors, and machine operators showed peak BC exposure levels surpassing 20 μg/m 3 , with average levels above 10 μg/m 3 . Despite their short exposure durations (<1 hour), these peaks contributed significantly (>60%) to the daily average BC exposure. The daily contribution rate of peak exposures above 10 μg/m 3 to the average daily BC exposure often exceeded 50%. The ratio of peak levels above 10 μg/m 3 and 50 μg/m 3 to the arithmetic mean was negatively correlated with exposure duration, the proportion of exposure duration, and the daily contribution of peak levels. Conclusion Drivers of diesel-engine vehicles often experienced significant spikes in BC exposure, highlighting the need for real-time monitoring, which is recommended as a best-practice approach to identify and mitigate short-term peak exposures.