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.

Background/Aims: Cardiovascular disease remains a major cause of mortality in patients with metabolic dysfunction-associated steatotic liver disease (MASLD). This study evaluated the association between subclinical carotid atherosclerosis (SCA) and MASLD or MASLD and increased alcohol intake (MetALD) in asymptomatic individuals. Methods: This cross-sectional study included 56,889 adults undergoing health check-ups in South Korea. Hepatic steatosis was diagnosed by ultrasound, and SCA was defined by carotid plaques or increased intima-media thickness. Liver fibrosis was evaluated using the fibrosis-4 index and elastography. Results: SCA was identified in 13.5%. MASLD and MetALD were significantly associated with SCA in models adjusted for demographic and lifestyle factors (adjusted odds ratio [aOR], 1.26;95% confidence interval [CI], 1.19 to 1.33; aOR, 1.43; 95% CI, 1.30 to 1.58; respectively, p<0.001for both). However, these associations attenuated and lost statistical significance when metabolic risk factors were further adjusted. The risk of SCA increased with greater hepatic steatosis and liver fibrosis severity. In patients with MASLD, aORs were 1.70 (hepatic steatosis index >36),1.23 (fibrosis-4 index ≥1.3), and 1.78 (liver stiffness measurement ≥5.6 kPa), compared to indi-viduals without MASLD. Similar trends were observed in the MetALD group. Additionally, hyper-tension and clustering of ≥3 cardiometabolic risk factors were significantly associated with SCA inthe MASLD group, supporting the role of metabolic burden in SCA development. Conclusions MASLD and MetALD were associated with increased SCA risk, particularly in individuals with hepatic steatosis and fibrosis. These findings suggest that metabolic burden and liver disease severity jointly contribute to subclinical atherosclerosis risk.

Heart failure (HF) prevalence and associated socio-economic costs have risen rapidly in Korea, creating urgent demand for a national, standardized prospective registry to support quality monitoring, outcome comparison, and real-world evidence. Standardized data definitions are essential for valid comparisons across studies and healthcare settings. We created a unified national HF cohort by integrating the two largest Korean registries, KorAHF (2011–2014;n=5,625) and KorHF III (2018–2023; n=7,351), yielding 12,976 hospitalized HF patients. Because heterogeneous variable definitions impeded direct comparisons, we implemented a harmonization pipeline across demographic, clinical, imaging, biomarker, therapeutic, and outcome domains, aligned with international standards and reinforced by systematic data quality checks.A multidisciplinary panel then conducted a structured decision process to produce the Korean HF Standard Dataset, a tiered and interoperable variable set spanning six domains: demographics, presentation at admission, in-hospital events and comorbidities, discharge status, outpatient follow-up, and readmission events. This integrated platform and standardized variables enable precise identification of HF patient phenotypes and prognostic factors, establishing an evidence-based foundation for disease management. This supports an analysis of temporal changes in treatment patterns and outcomes, generates data to inform future clinical practice guidelines, and provides a practical basis for planning large, continuous, prospective HF registries. Furthermore, it also facilitates pragmatic, registry-based randomized clinical trials and unmet-needs assessments that can guide national health policy. Establishing a foundation for future linkage with national health databases, this platform will allow for enhanced accuracy, comparability, and representativeness, powering quality improvement initiatives and population-level monitoring of Korea’s growing HF burden.

Purpose: This study aimed to develop and implement an antimicrobial stewardship education program for physician assistant nurses and to evaluate its effects on their knowledge and clinical performance. Methods: A quasi-experimental, single-group pre-post design was conducted with 50 physician assistant nurses at a university hospital in Seoul, Republic of Korea. The antimicrobial stewardship education program, developed using the ADDIE model, consisted of 12 sessions including lectures and case-based learning (CBL)-based discussions.Knowledge was measured before and immediately after the intervention, while performance was assessed pre-intervention and four weeks post-program. Data were analyzed using paired t-tests, Wilcoxon signed-rank tests, and analysis of covariance (ANCOVA). Results: Knowledge scores significantly improved from 44.65±7.45 to 58.50±10.11 (p<.001), and all subdomains showed significant increases (p<.001). Performance scores increased from 3.68±0.77 to 4.28±0.68 (p<.001). Knowledge gain did not differ significantly between the medical and surgical departments (p=.710). Likewise, after adjusting for pre-test scores, no significant difference in performance improvement was observed between the two departments (ANCOVA, p=.170). These results indicate that the program was effective across both departments regardless of their characteristics. Conclusion The antimicrobial stewardship education program improved both knowledge and performance among physician assistant nurses. This program may contribute to the standardization of antimicrobial stewardship education and to appropriate antimicrobial use and the reduction of antimicrobial resistance.

Background: The 16S rRNA-targeted next-generation sequencing (NGS) has been widely used as the primary tool for microbiome analysis. However, whether the sequenced microbial diversity absolutely represents the original sample composition remains unclear. This study aimed to evaluate whether 16S rRNA gene-targeted NGS accurately captures bacterial community composition. Methods: Mock communities were constructed using equal amounts of DNA from 18 bacterial strains in three formats: genomic DNA, recombinant plasmids, and polymerase chain reaction (PCR) templates. The V3V4 region of the 16S rRNA gene was amplified and sequenced using the Illumina MiSeq. Results: Data regression analysis revealed that the recombinant plasmid produced more accurate and precise correlation curve than that by the gDNA and PCR products, with a slope closest to 1 (1.0082) and the highest R² value (0.9975). Despite the same input amount of bacterial DNA, the NGS read distribution varied across all three mock communities. Using multiple regression analysis, we found that the guanine-cytosine (GC) content of the V3V4 region, 16S rRNA gene, size of gDNA, and copy number of 16S rRNA were significantly associated with the NGS output of each bacterial species. Conclusion This study demonstrated that recombinant plasmids are the preferred option for quality control and that NGS output is biased owing to certain bacterial characteristics, such as %GC content, gDNA size, and 16S rRNA gene copy number. Further research is required to develop a system that compensates for NGS process biases using mock communities.

Background: The 16S rRNA-targeted next-generation sequencing (NGS) has been widely used as the primary tool for microbiome analysis. However, whether the sequenced microbial diversity absolutely represents the original sample composition remains unclear. This study aimed to evaluate whether 16S rRNA gene-targeted NGS accurately captures bacterial community composition. Methods: Mock communities were constructed using equal amounts of DNA from 18 bacterial strains in three formats: genomic DNA, recombinant plasmids, and polymerase chain reaction (PCR) templates. The V3V4 region of the 16S rRNA gene was amplified and sequenced using the Illumina MiSeq. Results: Data regression analysis revealed that the recombinant plasmid produced more accurate and precise correlation curve than that by the gDNA and PCR products, with a slope closest to 1 (1.0082) and the highest R² value (0.9975). Despite the same input amount of bacterial DNA, the NGS read distribution varied across all three mock communities. Using multiple regression analysis, we found that the guanine-cytosine (GC) content of the V3V4 region, 16S rRNA gene, size of gDNA, and copy number of 16S rRNA were significantly associated with the NGS output of each bacterial species. Conclusion This study demonstrated that recombinant plasmids are the preferred option for quality control and that NGS output is biased owing to certain bacterial characteristics, such as %GC content, gDNA size, and 16S rRNA gene copy number. Further research is required to develop a system that compensates for NGS process biases using mock communities.

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.

Background: Malnutrition exacerbates the prognosis of numerous diseases; however, its specific impact on severe coronavirus disease 2019 (COVID-19) outcomes remains insufficiently explored. Methods: This multicenter study in Korea evaluated the nutritional status of 1,088 adults with severe COVID-19 using the Geriatric Nutritional Risk Index (GNRI) based on serum albumin levels and body weight. The patients were categorized into two groups: GNRI >98 (no-risk) and GNRI ≤98 (risk). Propensity score matching, adjusted for demographic and clinical variables, was conducted. Results: Of the 1,088 patients, 642 (59%) were classified as at risk of malnutrition. Propensity score matching revealed significant disparities in hospital (34.3% vs. 19.4%, p<0.001) and intensive care unit (ICU) mortality (31.5% vs. 18.9%, p<0.001) between the groups. The risk group was associated with a higher hospital mortality rate in the multivariate Cox regression analyses following propensity score adjustment (hazard ratio [HR], 1.64; p=0.001). Among the 670 elderly patients, 450 were at risk of malnutrition. Furthermore, the risk group demonstrated significantly higher hospital (52.1% vs. 29.5%, p<0.001) and ICU mortality rates (47.2% vs. 29.1%, p<0.001). The risk group was significantly associated with increased hospital mortality rates in the multivariate analyses following propensity score adjustment (HR, 1.66; p=0.001). Conclusion Malnutrition, as indicated by a low GNRI, was associated with increased mortality in patients with severe COVID-19. This effect was also observed in the elderly population. These findings underscore the critical importance of nutritional assessment and effective interventions for patients with severe COVID-19.

Background: The development of frailty at hospital discharge affects the clinical outcomes in severe coronavirus disease 2019 (COVID-19) survivors who had no frailty before hospitalization. We aimed to describe the prevalence of new frailty using the clinical frailty scale (CFS) and evaluate its associated factors in patients with severe COVID-19 without pre-existing frailty before hospitalization. Methods: We performed a secondary analysis of clinical data from a nationwide retrospective cohort collected from 22 hospitals between January 1, 2020 and August 31, 2021. The patients were at least 19 years old and survived until discharge after admission to the intensive care unit (ICU) because of severe COVID-19. Development of new frailty was defined as a CFS score ≥5 at hospital discharge. Results: Among 669 severe COVID-19 survivors without pre-existing frailty admitted to the ICU, the mean age was 65.2±12.8 years, 62.5% were male, and 50.2% received mechanical ventilation (MV). The mean CFS score at admission was 2.4±0.9, and new frailty developed in 27.8% (186/483). In multivariate analysis, older age, cardiovascular disease, CFS score of 3–4 before hospitalization, increased C-reactive protein level, longer duration of corticosteroid treatment, and use of MV and extracorporeal membrane oxygenation were identified as factors associated with new-onset frailty. Conclusion Our study suggests that new frailty is not uncommon and is associated with diverse factors in survivors of severe COVID-19 without pre-existing frailty.

Background: Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive lung disease that culminates in respiratory failure and death due to irreversible scarring of the distal lung. While initially considered a chronic inflammatory disorder, the aberrant function of the alveolar epithelium is now acknowledged as playing a central role in the pathophysiology of IPF. This study aimed to investigate the regenerative capacity of alveolar type 2 (AT2) cells using IPF-derived alveolar organoids and to examine the effects of disease progression on this capacity. Methods: Lung tissues from three pneumothorax patients and six IPF patients (early and advanced stages) were obtained through video-assisted thoracoscopic surgery and lung transplantation. HTII-280+ cells were isolated from CD31-CD45-epithelial cell adhesion molecule (EpCAM)+ cells in the distal lungs of IPF and pneumothorax patients using fluorescence-activated cell sorting (FACS) and resuspended in 48-well plates to establish IPF-derived alveolar organoids. Immunostaining was used to verify the presence of AT2 cells. Results: FACS sorting yielded approximately 1% of AT2 cells in early IPF tissue, and the number decreased as the disease progressed, in contrast to 2.7% in pneumothorax. Additionally, the cultured organoids in the IPF groups were smaller and less numerous compared to those from pneumothorax patients. The colony forming efficiency decreased as the disease advanced. Immunostaining results showed that the IPF organoids expressed less surfactant protein C (SFTPC) compared to the pneumothorax group and contained keratin 5+ (KRT5+) cells. Conclusion This study confirmed that the regenerative capacity of AT2 cells in IPF decreases as the disease progresses, with IPF-derived AT2 cells inherently exhibiting functional abnormalities and altered differentiation plasticity.