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.

Purpose: While TP53 mutations are well known to be associated with adverse prognosis in hematological diseases, their functional impact remains incompletely understood. This study examines the spectrum of TP53 mutations across various hematologic malignancies and evaluates their functional impact. Materials and Methods: Using targeted sequencing panels, we analyzed TP53 mutations in the bone marrow aspiration samples of a retrospective cohort of 856 patients diagnosed with hematologic malignancies. To assess the impact of TP53 mutations, we applied the evolutionary action (EAp53) score and the relative fitness score (RFS), previously proposed functional scoring methods. The effects of variant allele frequency (VAF), disruptive mutations, EAp53 score, and RFS on overall survival (OS) were evaluated. Results: TP53 mutations were associated with inferior OS compared with wildtype TP53 (median OS 10.0 months versus not estimable; hazard ratio (HR) 4.6; p<0.001). In the acute myeloid leukemia, multiple myeloma, and myelodysplastic syndrome subgroups, TP53 mutations had a significant adverse impact on OS. (HRs 3.8, 4.2, 6.0, respectively; p<0.001, p=0.005, p<0.001, respectively). Patients with VAF >50% had significantly poorer OS compared to those with VAF ≤50% (median OS 7.5 months versus 22.8 months; HR 2.2, p=0.016). Moreover, patients in the high-risk RFS group (RFS >0.22) had significantly worse OS compared to those in the low-risk RFS group (RFS ≤0.22) (median OS 5.6 months versus 16.3 months; HR 2.2, p=0.041). However, no significant survival difference was observed between the EAp53 high-risk (>75) and low-risk (≤75) groups, or between patients with disruptive and non-disruptive mutations. Conclusion Our findings highlight VAF and RFS as valuable tools for stratifying TP53-mutant patients into high-risk and low-risk groups.

Purpose: The aim of this study is to compare the detection ability of quality of life (QoL) changes and responsiveness of the KOrean QUality of life in Stomach cancer patients Study group (KOQUSS)-40 and European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ). Materials and Methods: A multicenter prospective observational study was conducted to evaluate QoL changes after various gastrectomies between January 2021 and April 2022. Participants were instructed to complete the KOQUSS-40 and EORTC QLQ-C30/STO22 preoperatively and at 1, 3, 6, and 12 months postoperatively. QoL changes over time and QoL responsiveness were assessed for each questionnaire. Results: Data from 491 patients who underwent curative gastrectomy for gastric cancer at 22 institutions were analyzed. The summary scores of the KOQUSS-40 and EORTC QLQ-STO22 showed significant differences between the total and proximal gastrectomy groups (p=0.044 and p=0.038, respectively), but no difference was observed for the EORTC QLQ-C30. Dysphagia on the KOQUSS-40 was significantly different between the total and proximal gastrectomy groups (p=0.031); however, dysphagia on the EORTC QLQ-STO22 did not differ. The responsiveness of the KOQUSS-40 was similar to that of the EORTC QLQ in patients who experienced ≥ 10% body weight loss, but approximately 10% less in patients receiving adjuvant chemotherapy than the EORTC QLQ. Conclusion KOQUSS-40 has several advantages over EORTC QLQ-C30/STO22 when comparing QoL between the total and proximal gastrectomy groups. The findings provide information for researchers investigating the QoL of patients who have undergone curative gastrectomy for gastric cancer.

Pharmacogenomic variations may significantly influence responses to commonly prescribed stroke medications. Despite accumulating evidence, genetic testing has not yet been widely integrated into stroke care. This review summarizes current evidence and provides practical guidance for clinical implementation. Pharmacogenomic studies and clinical guidelines related to antiplatelet agents, anticoagulants, and statins were reviewed, with particular emphasis on East Asian populations. Substantial evidence supports genotype-guided use of clopidogrel (CYP2C19), warfarin (CYP2C9, VKORC1, CYP4F2), and statins (SLCO1B1, ABCG2). For aspirin, PTGS1/2 and PEAR1 variants have been investigated; however, current data remain insufficient for clinical application. Regarding direct oral anticoagulants (DOACs), candidate genes such as ABCB1 and CES1 demonstrate pharmacokinetic associations, though robust clinical outcome data are lacking. Distinct allele frequencies in East Asians—such as higher prevalence of CYP2C19 and ABCG2 variants—underscore the need for population-specific strategies. Beyond single-gene approaches, polygenic risk scores, pharmacogenomic panels, and integration with multi-omics data and artificial intelligence represent promising directions for personalized therapy. Pharmacogenomic testing can enhance stroke pharmacotherapy, particularly in populations with high frequencies of actionable variants. Broader implementation requires rapid testing platforms, clinician education, tailored clinical guidelines, and real-world validation of aspirin, DOACs, and multi-gene approaches. Future research should expand population-specific studies and integrate pharmacogenomics within the broader framework of precision medicine to ensure equitable clinical benefit.

Objectives: This study aimed to investigate the prevalence of depressive symptoms among hospital nurses and their associations with psychosocial and job-related factors. Methods: A total of 515 nurses at one university hospital participated in this study. Data on demographics, job-related factors, burnout, social conflict, happiness, and ego-resiliency were collected using self-reported questionnaires. Depressive symptoms were assessed using the depressive subscale of the Hospital Anxiety and Depression Scale, with scores of 8 or higher indicating their presence. Demographics, job-related, and psychosocial factors were compared based on the presence of depressive symptoms. Logistic regression analysis was conducted to identify factors associated with depressive symptoms. In addition, the mediating effect of ego-resiliency on the relationship between burnout and depressive symptoms was examined. Results: A total of 226 participants (43.9%) were identified as having depressive symptoms. Happiness was associated with a lower risk of depressive symptoms, whereas burnout and social conflict were associated with a higher risk. Furthermore, ego-resiliency showed a significant mediating effect on the relationship between burnout and depressive symptoms. Being a basic or charge nurse; experiencing job dissatisfaction; being exposed to higher levels of burnout and social conflict; and having lower levels of happiness and ego-resiliency were significantly correlated with depressive symptoms. Conclusions Our findings suggest that intervention strategies aimed at enhancing happiness and ego-resiliency while reducing burnout and social conflict may help prevent and manage depressive symptoms among hospital nurses.

Objectives: Large language models (LLMs) demonstrate remarkable potential in healthcare communication. However, whether they can process complex, high-volume medical information, such as stroke-related content, remains insufficiently validated. This study aimed to evaluate the natural language processing capabilities of LLMs in handling such content and to develop an evaluation instrument. Methods: A survey compared educational materials generated by two LLMs (ChatGPT 4.0 and Claude 3) with neurologist-authored content on stroke. The materials were based on two clinical scenarios representing distinct stroke etiologies: cardioembolism and large-artery atherosclerosis. They were evaluated in terms of accuracy, legality, ethics, comprehensiveness, and information delivery. Scores for comprehensiveness and information delivery were compared according to participants’ agreement with the use of LLMs in healthcare. Results: ChatGPT received the highest scores across all domains, except for legality in Scenario 2. In Scenario 1, the ranking for accuracy and summarization of clinical information was, from highest to lowest, ChatGPT, Claude, and the neurologist (η2 = 0.140, p < 0.001; η2 = 0.175, p < 0.001). The same hierarchy was observed in Scenario 2 for accuracy (η2 = 0.077, p < 0.001) and summarization (η2 = 0.194, p < 0.001). Participants who agreed with the use of LLMs in healthcare assigned higher scores for the comprehensiveness (Scenario 1, p = 0.005; Scenario 2, p = 0.007) and information delivery (Scenario 1, p = 0.003; Scenario 2, p = 0.026) of ChatGPT-generated materials than participants who did not agree. Conclusions LLMs demonstrated adequate capability to convey complex content, such as stroke-related information, in an accessible and understandable manner for non-experts.

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 and Objectives: Graves’ ophthalmopathy (GO) is an autoimmune inflammatory disorder that can adversely affect quality of life in patients with Graves’ disease (GD). The objective of this study was to characterize the clinical features of patients with GO and to identify risk factors associated with its development and the need for anti-inflammatory treatment. Materials and Methods: In this multicenter, retrospective observational study, 818 patients with GD were identified via electronic medical record review. Clinical characteristics were assessed, and logistic regression analyses were performed to identify risk factors for GO development and the need for anti-inflammatory treatment. Results: Among the 818 patients with GD, 135 (16.5%) developed GO, and 60 (7.3%) of these patients received anti-inflammatory treatment. GO was diagnosed at the time of GD diagnosis in 54.8% of cases, and proptosis and eyelid/orbital swelling were the common presenting features. In multivariable analysis, female sex (odds ratio [OR]: 1.75, confidence interval [CI]: 1.02-3.03), goiter (OR: 1.71, CI: 1.08-2.71), and smoking (ex-smokers: OR, 2.18; 95% CI: 1.02-4.65; current smokers: OR, 3.11; CI, 1.78-5.44) were independently associated with GO development, whereas diabetes (OR: 0.35, CI: 0.14-0.89) was inversely associated. Higher total cholesterol (OR: 1.31, CI: 1.01-1.04) and elevated thyrotropin-binding inhibitory immunoglobulin levels (OR: 1.07, CI: 1.02-1.11) were also significantly associated with the need for anti-inflammatory treatment. Conclusion This study delineated the clinical features of GO and identified risk factors for its development and the need for anti-inflammatory treatment in patients with GD, providing valuable information for the management of GO in Korean patients.