Purpose: Adjuvant chemotherapy (AC) is recommended for muscle-invasive or lymph node-positive upper urinary tract urothelial carcinoma (UTUC) after radical nephroureterectomy (RNU). However, disease recurrences are frequently observed in pT1 disease, and AC may increase the risk of overtreatment in pT2 UTUC patients. This study aimed to validate a risk-adapted scoring model for selecting UTUC patients with ≤pT2 disease who would benefit from AC. Materials and Methods: We retrospectively analyzed 443 ≤pT2 UTUC patients who underwent RNU. A risk-adapted scoring model was applied, categorizing patients into low- or high-risk groups. Recurrence-free survival (RFS) and cancer-specific survival (CSS) were analyzed according to risk group. Results: Overall, 355 patients (80.1%) and 88 patients (19.9%) were categorized into the low- and high-risk groups, respectively, with the latter having higher pathological stages, concurrent carcinoma in situ, and synchronous bladder tumors. Disease recurrence occurred in 45 patients (10.2%), among whom 19 (5.4%) and 26 (29.5%) belonged to the low- and high-risk groups, respectively (p<0.001). High-risk patients had significantly shorter RFS (64.3% vs. 93.6% at 60 months; hazard ratio [HR] 13.66; p<0.001) and worse CSS (80.7% vs. 91.5% at 60 months; HR 4.25; p=0.002). Multivariate analysis confirmed that pT2 stage and the high-risk group were independent predictors of recurrence and cancer-specific death (p<0.001). Decision curve analysis for RFS showed larger net benefits with our model than with the T stage model. Conclusions The risk-adapted scoring model effectively predicts recurrence and identifies optimal candidates for AC post RNU in non-metastatic UTUC.

Purpose: This study compared the diagnostic performance of quantitative ultrasonography (QUS) with that of conventional ultrasonography (US) in assessing hepatic steatosis among individuals undergoing health screening using magnetic resonance imaging–derived proton density fat fraction (MRI-PDFF) as the reference standard. Methods: This single-center prospective study enrolled 427 participants who underwent abdominal MRI and US. Measurements included the attenuation coefficient in tissue attenuation imaging (TAI) and the scatter-distribution coefficient in tissue scatter-distribution imaging (TSI). The correlation between QUS and MRI-PDFF was evaluated. The diagnostic capabilities of QUS, conventional B-mode US, and their combined models for detecting hepatic fat content of ≥5% (MRI-PDFF ≥5%) and ≥10% (MRI-PDFF ≥10%) were compared by analyzing the areas under the receiver operating characteristic curves. Additionally, clinical risk factors influencing the diagnostic performance of QUS were identified using multivariate linear regression analyses. Results: TAI and TSI were strongly correlated with MRI-PDFF (r=0.759 and r=0.802, respectively; both P<0.001) and demonstrated good diagnostic performance in detecting and grading hepatic steatosis. The combination of QUS and B-mode US resulted in the highest areas under the ROC curve (AUCs) (0.947 and 0.975 for detecting hepatic fat content of ≥5% and ≥10%, respectively; both P<0.05), compared to TAI, TSI, or B-mode US alone (AUCs: 0.887, 0.910, 0.878 for ≥5% and 0.951, 0.922, 0.875 for ≥10%, respectively). The independent determinants of QUS included skinliver capsule distance (β=7.134), hepatic fibrosis (β=4.808), alanine aminotransferase (β=0.202), triglyceride levels (β=0.027), and diabetes mellitus (β=3.710). Conclusion QUS is a useful and effective screening tool for detecting and grading hepatic steatosis during health checkups.

Purpose: This study compared the diagnostic performance of quantitative ultrasonography (QUS) with that of conventional ultrasonography (US) in assessing hepatic steatosis among individuals undergoing health screening using magnetic resonance imaging–derived proton density fat fraction (MRI-PDFF) as the reference standard. Methods: This single-center prospective study enrolled 427 participants who underwent abdominal MRI and US. Measurements included the attenuation coefficient in tissue attenuation imaging (TAI) and the scatter-distribution coefficient in tissue scatter-distribution imaging (TSI). The correlation between QUS and MRI-PDFF was evaluated. The diagnostic capabilities of QUS, conventional B-mode US, and their combined models for detecting hepatic fat content of ≥5% (MRI-PDFF ≥5%) and ≥10% (MRI-PDFF ≥10%) were compared by analyzing the areas under the receiver operating characteristic curves. Additionally, clinical risk factors influencing the diagnostic performance of QUS were identified using multivariate linear regression analyses. Results: TAI and TSI were strongly correlated with MRI-PDFF (r=0.759 and r=0.802, respectively; both P<0.001) and demonstrated good diagnostic performance in detecting and grading hepatic steatosis. The combination of QUS and B-mode US resulted in the highest areas under the ROC curve (AUCs) (0.947 and 0.975 for detecting hepatic fat content of ≥5% and ≥10%, respectively; both P<0.05), compared to TAI, TSI, or B-mode US alone (AUCs: 0.887, 0.910, 0.878 for ≥5% and 0.951, 0.922, 0.875 for ≥10%, respectively). The independent determinants of QUS included skinliver capsule distance (β=7.134), hepatic fibrosis (β=4.808), alanine aminotransferase (β=0.202), triglyceride levels (β=0.027), and diabetes mellitus (β=3.710). Conclusion QUS is a useful and effective screening tool for detecting and grading hepatic steatosis during health checkups.

Purpose: This study compared the diagnostic performance of quantitative ultrasonography (QUS) with that of conventional ultrasonography (US) in assessing hepatic steatosis among individuals undergoing health screening using magnetic resonance imaging–derived proton density fat fraction (MRI-PDFF) as the reference standard. Methods: This single-center prospective study enrolled 427 participants who underwent abdominal MRI and US. Measurements included the attenuation coefficient in tissue attenuation imaging (TAI) and the scatter-distribution coefficient in tissue scatter-distribution imaging (TSI). The correlation between QUS and MRI-PDFF was evaluated. The diagnostic capabilities of QUS, conventional B-mode US, and their combined models for detecting hepatic fat content of ≥5% (MRI-PDFF ≥5%) and ≥10% (MRI-PDFF ≥10%) were compared by analyzing the areas under the receiver operating characteristic curves. Additionally, clinical risk factors influencing the diagnostic performance of QUS were identified using multivariate linear regression analyses. Results: TAI and TSI were strongly correlated with MRI-PDFF (r=0.759 and r=0.802, respectively; both P<0.001) and demonstrated good diagnostic performance in detecting and grading hepatic steatosis. The combination of QUS and B-mode US resulted in the highest areas under the ROC curve (AUCs) (0.947 and 0.975 for detecting hepatic fat content of ≥5% and ≥10%, respectively; both P<0.05), compared to TAI, TSI, or B-mode US alone (AUCs: 0.887, 0.910, 0.878 for ≥5% and 0.951, 0.922, 0.875 for ≥10%, respectively). The independent determinants of QUS included skinliver capsule distance (β=7.134), hepatic fibrosis (β=4.808), alanine aminotransferase (β=0.202), triglyceride levels (β=0.027), and diabetes mellitus (β=3.710). Conclusion QUS is a useful and effective screening tool for detecting and grading hepatic steatosis during health checkups.

Purpose: This study compared the diagnostic performance of quantitative ultrasonography (QUS) with that of conventional ultrasonography (US) in assessing hepatic steatosis among individuals undergoing health screening using magnetic resonance imaging–derived proton density fat fraction (MRI-PDFF) as the reference standard. Methods: This single-center prospective study enrolled 427 participants who underwent abdominal MRI and US. Measurements included the attenuation coefficient in tissue attenuation imaging (TAI) and the scatter-distribution coefficient in tissue scatter-distribution imaging (TSI). The correlation between QUS and MRI-PDFF was evaluated. The diagnostic capabilities of QUS, conventional B-mode US, and their combined models for detecting hepatic fat content of ≥5% (MRI-PDFF ≥5%) and ≥10% (MRI-PDFF ≥10%) were compared by analyzing the areas under the receiver operating characteristic curves. Additionally, clinical risk factors influencing the diagnostic performance of QUS were identified using multivariate linear regression analyses. Results: TAI and TSI were strongly correlated with MRI-PDFF (r=0.759 and r=0.802, respectively; both P<0.001) and demonstrated good diagnostic performance in detecting and grading hepatic steatosis. The combination of QUS and B-mode US resulted in the highest areas under the ROC curve (AUCs) (0.947 and 0.975 for detecting hepatic fat content of ≥5% and ≥10%, respectively; both P<0.05), compared to TAI, TSI, or B-mode US alone (AUCs: 0.887, 0.910, 0.878 for ≥5% and 0.951, 0.922, 0.875 for ≥10%, respectively). The independent determinants of QUS included skinliver capsule distance (β=7.134), hepatic fibrosis (β=4.808), alanine aminotransferase (β=0.202), triglyceride levels (β=0.027), and diabetes mellitus (β=3.710). Conclusion QUS is a useful and effective screening tool for detecting and grading hepatic steatosis during health checkups.

Purpose: This study compared the diagnostic performance of quantitative ultrasonography (QUS) with that of conventional ultrasonography (US) in assessing hepatic steatosis among individuals undergoing health screening using magnetic resonance imaging–derived proton density fat fraction (MRI-PDFF) as the reference standard. Methods: This single-center prospective study enrolled 427 participants who underwent abdominal MRI and US. Measurements included the attenuation coefficient in tissue attenuation imaging (TAI) and the scatter-distribution coefficient in tissue scatter-distribution imaging (TSI). The correlation between QUS and MRI-PDFF was evaluated. The diagnostic capabilities of QUS, conventional B-mode US, and their combined models for detecting hepatic fat content of ≥5% (MRI-PDFF ≥5%) and ≥10% (MRI-PDFF ≥10%) were compared by analyzing the areas under the receiver operating characteristic curves. Additionally, clinical risk factors influencing the diagnostic performance of QUS were identified using multivariate linear regression analyses. Results: TAI and TSI were strongly correlated with MRI-PDFF (r=0.759 and r=0.802, respectively; both P<0.001) and demonstrated good diagnostic performance in detecting and grading hepatic steatosis. The combination of QUS and B-mode US resulted in the highest areas under the ROC curve (AUCs) (0.947 and 0.975 for detecting hepatic fat content of ≥5% and ≥10%, respectively; both P<0.05), compared to TAI, TSI, or B-mode US alone (AUCs: 0.887, 0.910, 0.878 for ≥5% and 0.951, 0.922, 0.875 for ≥10%, respectively). The independent determinants of QUS included skinliver capsule distance (β=7.134), hepatic fibrosis (β=4.808), alanine aminotransferase (β=0.202), triglyceride levels (β=0.027), and diabetes mellitus (β=3.710). Conclusion QUS is a useful and effective screening tool for detecting and grading hepatic steatosis during health checkups.

Viral load and the duration of viral shedding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are important determinants of the transmission of coronavirus disease 2019.In this study, we examined the effects of viral doses on the lung and spleen of K18-hACE2 transgenic mice by temporal histological and transcriptional analyses. Approximately, 1×105 plaque-forming units (PFU) of SARS-CoV-2 induced strong host responses in the lungs from 2 days post inoculation (dpi) which did not recover until the mice died, whereas responses to the virus were obvious at 5 days, recovering to the basal state by 14 dpi at 1×102 PFU. Further, flow cytometry showed that number of CD8+ T cells continuously increased in 1×102 PFU-virusinfected lungs from 2 dpi, but not in 1×105 PFU-virus-infected lungs. In spleens, responses to the virus were prominent from 2 dpi, and number of B cells was significantly decreased at 1×105PFU; however, 1×102 PFU of virus induced very weak responses from 2 dpi which recovered by 10 dpi. Although the defense responses returned to normal and the mice survived, lung histology showed evidence of fibrosis, suggesting sequelae of SARS-CoV-2 infection. Our findings indicate that specific effectors of the immune response in the lung and spleen were either increased or depleted in response to doses of SARS-CoV-2. This study demonstrated that the response of local and systemic immune effectors to a viral infection varies with viral dose, which either exacerbates the severity of the infection or accelerates its elimination.

Cardio-oncology is a critical field due to the escalating significance of cardiovascular toxicity as a side effect of anti‑ cancer treatments. Cancer therapy-related cardiac dysfunction (CTRCD) is a prevalent condition associated with car‑ diovascular toxicity, necessitating effective strategies for prediction, monitoring, management, and tracking. This comprehensive review examines the definition and risk stratification of CTRCD, explores monitoring approaches during anticancer therapy, and highlights specific cardiovascular toxicities linked to various cancer treatments. These include anthracyclines, HER2-targeted agents, vascular endothelial growth factor inhibitors, immune checkpoint inhibitors, chimeric antigen receptor T-cell therapies, and tumor-infiltrating lymphocytes therapies. Incorporating the Korean data, this review offers insights into the regional nuances in managing CTRCD. Using systematic follow-up incorporating cardiovascular imaging and biomarkers, a better understanding and management of CTRCD can be achieved, optimizing the cardiovascular health of both cancer patients and survivors.

Background: There is a need to update the cardiovascular (CV) Sequential Organ Failure Assessment (SOFA) score to reflect the current practice in sepsis. We previously proposed the modified CV SOFA score from data on blood pressure, norepinephrine equivalent dose, and lactate as gathered from emergency departments. In this study, we externally validated the modified CV SOFA score in multicenter intensive care unit (ICU) patients. Methods: A multicenter retrospective observational study was conducted on ICU patients at six hospitals in Korea. We included adult patients with sepsis who were admitted to ICUs. We compared the prognostic performance of the modified CV/total SOFA score and the original CV/total SOFA score in predicting 28-day mortality. Discrimination and calibration were evaluated using the area under the receiver operating characteristic curve (AUROC) and the calibration curve, respectively. Results: We analyzed 1,015 ICU patients with sepsis. In overall patients, the 28-day mortality rate was 31.2%. The predictive validity of the modified CV SOFA (AUROC, 0.712; 95% confidence interval [CI], 0.677–0.746; P < 0.001) was significantly higher than that of the original CV SOFA (AUROC, 0.644; 95% CI, 0.611–0.677). The predictive validity of modified total SOFA score for 28-day mortality was significantly higher than that of the original total SOFA (AUROC, 0.747 vs. 0.730; 95% CI, 0.715–0.779; P = 0.002). The calibration curve of the original CV SOFA for 28-day mortality showed poor calibration. In contrast, the calibration curve of the modified CV SOFA for 28-day mortality showed good calibration. Conclusion In patients with sepsis in the ICU, the modified SOFA score performed better than the original SOFA score in predicting 28-day mortality.

Objective: Although nonsteroidal anti-inflammatory drugs (NSAIDs) are the first-line treatment for ankylosing spondylitis (AS), their effect on kidney function remains unclear. This longitudinal study investigated the correlation between long-term NSAID use and kidney function in patients with AS using electronic medical records. Methods: The electronic medical records of 1,280 patients with AS collected from a single center between January 2001 and December 2018 were reviewed. The Assessment of Spondyloarthritis International Society (ASAS) NSAID Intake Score was used to determine the cumulative dose of all NSAIDs prescribed for a different time intervals. Each ASAS NSAID Intake Score was obtained for intervals of 6 months, 1 year, 2 years, 3 years, 5 years, and 10 years. The correlation between the ASAS NSAID Intake Score and final estimated glomerular filtration rate (eGFR) for each interval was investigated. Results: The mean ASAS Intake Scores for 6-month, 1-year, 2-year, 3-year, 5-year, and 10-year intervals were 55.30, 49.28, 44.84, 44.14, 44.61, and 41.17, respectively. At each interval, the pearson correlation coefficients were −0.018 (95% CI: −0.031 to −0.006, p=0.004), −0.021 (95% CI: −0.039 to −0.004, p=0.018), −0.045 (95% CI: −0.071 to −0.019, p=0.001), −0.069 (95% CI: −0.102 to −0.037, p<0.001), −0.070 (95% CI: −0.114 to −0.026, p=0.002), −0.019 (95% CI: −0.099 to 0.062, p=0.645), respectively. There was a very weak negative relationship between ASAS Intake Score and eGFR at each interval. Conclusion Long-term NSAID use did not correlate with kidney function based on real-world data in patients with AS.