Objective: Double microcatheter technique (dMC) can be the alternative to Single microcatheter technique (sMC) for challenging cases, but there is lack of studies comparing dMC to sMC especifically for small ruptured aneurysms. Our objective was to compare the safety and efficacy of dMC to sMC in treating small (≤5 mm) and tiny (≤3 mm) ruptured aneurysms. Methods: This study focused on 91 out of 280 patients who had ruptured aneurysms and underwent either single or double microcatheter coil embolization. These patients were treated with either single or double microcatheter coil embolization. We divided the patients into two groups based on the procedural method and evaluated clinical features and outcomes. Subgroup analyses were conducted specifically for tiny aneurysms, comparing the two methods, and within the dMC group, we also examined whether the aneurysm was tiny or not. In addition, univariate logistic regression analysis was performed to assess the impact of coil packing density. Results: The mean values for most outcome measures in the dMC group were higher than those in the sMC group, but these differences did not reach statistical significance (coil packing density, 45.739% vs. 39.943%; procedural complication, 4.17% vs. 11.94%; recanalization, 8.3% vs. 10.45%; discharge discharge modified Rankin Scale (mRS), 1.83 vs. 1.97). The comparison between tiny aneurysms and other sizes within the dMC group did not reveal any significant differences in terms of worse outcomes or increased risk. The only factor that significantly influenced coil packing density in the univariate logistic regression analysis was the size of the aneurysm (OR 0.309, 95% CI 0.169–0.566, p=0.000). Conclusions The dMC proved to be a safe and viable alternative to the sMC for treating small ruptured aneurysms in challenging cases.

Background: Worldwide, sepsis is the leading cause of death in hospitals. If mortality rates in patients with sepsis can be predicted early, medical resources can be allocated efficiently. We constructed machine learning (ML) models to predict the mortality of patients with sepsis in a hospital emergency department. Methods: This study prospectively collected nationwide data from an ongoing multicenter cohort of patients with sepsis identified in the emergency department. Patients were enrolled from 19 hospitals between September 2019 and December 2020. For acquired data from 3,657 survivors and 1,455 deaths, six ML models (logistic regression, support vector machine, random forest, extreme gradient boosting [XGBoost], light gradient boosting machine, and categorical boosting [CatBoost]) were constructed using fivefold cross-validation to predict mortality. Through these models, 44 clinical variables measured on the day of admission were compared with six sequential organ failure assessment (SOFA) components (PaO 2 /FIO 2 [PF], platelets (PLT), bilirubin, cardiovascular, Glasgow Coma Scale score, and creatinine).The confidence interval (CI) was obtained by performing 10,000 repeated measurements via random sampling of the test dataset. All results were explained and interpreted using Shapley’s additive explanations (SHAP). Results: Of the 5,112 participants, CatBoost exhibited the highest area under the curve (AUC) of 0.800 (95% CI, 0.756–0.840) using clinical variables. Using the SOFA components for the same patient, XGBoost exhibited the highest AUC of 0.678 (95% CI, 0.626–0.730). As interpreted by SHAP, albumin, lactate, blood urea nitrogen, and international normalization ratio were determined to significantly affect the results. Additionally, PF and PLTs in the SOFA component significantly influenced the prediction results. Conclusion Newly established ML-based models achieved good prediction of mortality in patients with sepsis. Using several clinical variables acquired at the baseline can provide more accurate results for early predictions than using SOFA components. Additionally, the impact of each variable was identified.

This study aimed to evaluate the differences in the baseline characteristics and patterns of antibiotic usage among hospitals based on their participation in the Korea National Antimicrobial Use Analysis System (KONAS). We obtained claims data from the National Health Insurance for inpatients admitted to all secondary- and tertiary-care hospitals between January 2020 and December 2021 in Korea. 15.9% (58/395) of hospitals were KONAS participants, among which the proportion of hospitals with > 900 beds (31.0% vs.2.6%, P < 0.001) and tertiary care (50.0% vs. 5.2%, P < 0.001) was higher than that among non-participants. The consumption of antibiotics targeting antimicrobial-resistant gram positive bacteria (33.7 vs. 27.1 days of therapy [DOT]/1,000 patient-days, P = 0.019) and antibiotics predominantly used for resistant gram-negative bacteria (4.8 vs. 3.7 DOT/1,000 patient-days, P = 0.034) was higher in KONAS-participating versus -non-participating hospitals. The current KONAS data do not fully represent all secondary- and tertiary-care hospitals in Korea; thus, the KONAS results should be interpreted with caution.

Objective: To investigate whether reader training improves the performance and agreement of radiologists in interpreting unenhanced breast magnetic resonance imaging (MRI) scans using diffusion-weighted imaging (DWI). Materials and Methods: A study of 96 breasts (35 cancers, 24 benign, and 37 negative) in 48 asymptomatic women was performed between June 2019 and October 2020. High-resolution DWI with b-values of 0, 800, and 1200 sec/mm 2 was performed using a 3.0-T system. Sixteen breast radiologists independently reviewed the DWI, apparent diffusion coefficient maps, and T1-weighted MRI scans and recorded the Breast Imaging Reporting and Data System (BI-RADS) category for each breast. After a 2-h training session and a 5-month washout period, they re-evaluated the BI-RADS categories. A BI-RADS category of 4 (lesions with at least two suspicious criteria) or 5 (more than two suspicious criteria) was considered positive.The per-breast diagnostic performance of each reader was compared between the first and second reviews. Inter-reader agreement was evaluated using a multi-rater κ analysis and intraclass correlation coefficient (ICC). Results: Before training, the mean sensitivity, specificity, and accuracy of the 16 readers were 70.7% (95% confidence interval [CI]: 59.4–79.9), 90.8% (95% CI: 85.6–94.2), and 83.5% (95% CI: 78.6–87.4), respectively. After training, significant improvements in specificity (95.2%; 95% CI: 90.8–97.5; P = 0.001) and accuracy (85.9%; 95% CI: 80.9–89.8; P = 0.01) were observed, but no difference in sensitivity (69.8%; 95% CI: 58.1–79.4; P = 0.58) was observed. Regarding inter-reader agreement, the κ values were 0.57 (95% CI: 0.52–0.63) before training and 0.68 (95% CI: 0.62–0.74) after training, with a difference of 0.11 (95% CI: 0.02–0.18; P = 0.01). The ICC was 0.73 (95% CI: 0.69–0.74) before training and 0.79 (95% CI: 0.76–0.80) after training (P = 0.002). Conclusion Brief reader training improved the performance and agreement of interpretations by breast radiologists using unenhanced MRI with DWI.

Purpose: Orbital fibroblasts play key roles in the pathogenesis of Graves’ orbitopathy (GO), and previous findings have shown that endoplasmic reticulum (ER) stress and autophagy also contribute to GO. In this study, we investigated the presently unclear roles of inositol-requiring enzyme 1 (IRE1) and related autophagy processes in the pro-fibrotic mechanism of GO. Materials and Methods: Orbital adipose/connective tissues were obtained from eight GO patients and six normal individuals during surgery. GO fibroblasts were transfected with IRE1 small-interfering RNA and treated with bafilomycin A1 (Baf-A1) to evaluate the inhibitory effects of ER stress and autophagy, and protein-expression levels were analyzed through western blotting after stimulation with transforming growth factor (TGF)-β. Results: TGF-β stimulation upregulated IRE1 in GO orbital fibroblasts, whereas silencing IRE1 suppressed fibrosis and autophagy responses. Similarly, Baf-A1, an inhibitor of late-phase autophagy, decreased the expression of pro-fibrotic proteins. Conclusion IRE1 mediates autophagy and the pro-fibrotic mechanism of GO, which provides a more comprehensive interpretation of GO pathogenesis and suggests potential therapeutic targets.

Purpose: The treatment of male breast cancer (MBC) has been extrapolated from female breast cancer (FBC) because of its rarity despite their different clinicopathologic characteristics. We aimed to investigate the distribution of intrinsic subtypes based on immunohistochemistry, their clinical impact, and treatment pattern in clinical practice through a multicenter study in Korea. Materials and Methods: We retrospectively analyzed clinical data of 248 MBC patients from 18 institutions across the country from January 1995 to July 2016. Results: The median age of MBC patients was 63 years (range, 25 to 102 years). Among 148 intrinsic subtype classified patients, 61 (41.2%), 44 (29.7%), 29 (19.5%), and 14 (9.5%) were luminal A, luminal B, human epidermal growth factor receptor 2, and triple-negative breast cancer, respectively. Luminal A subtype showed trends for superior survival compared to other subtypes. Most hormone receptor-positive patients (166 patients, 82.6%) received adjuvant endocrine treatment. Five-year completion of adjuvant endocrine treatment was associated with superior disease-free survival (DFS) in patients classified with an intrinsic subtype (hazard ratio [HR], 0.15; 95% confidence interval [CI], 0.04 to 0.49; p=0.002) and in all patients (HR, 0.16; 95% CI, 0.05 to 0.54; p=0.003). Conclusion Distribution of subtypes of MBC was similar to FBC and luminal type A was most common. Overall survival tended to be improved for luminal A subtype, although there was no statistical significance. Completion of adjuvant endocrine treatment was associated with prolonged DFS in intrinsic subtype classified patients. MBC patients tended to receive less treatment. MBC patients should receive standard treatment according to guidelines as FBC patients.

Background: Phospholipase C-γ (PLC-γ) plays a crucial role in immune responses and is related to the pathogenesis of various inflammatory disorders. In this study, we investigated the role of PLC-γ and the therapeutic effect of the PLC-specific inhibitor U73122 using orbital fibroblasts from patients with Graves’ orbitopathy (GO). Methods: The expression of phospholipase C gamma 1 (PLCG1) and phospholipase C gamma 2 (PLCG2) was evaluated using polymerase chain reaction in GO and normal orbital tissues/fibroblasts. The primary cultures of orbital fibroblasts were treated with non-toxic concentrations of U73122 with or without interleukin (IL)-1β to determine its therapeutic efficacy. The proinflammatory cytokine levels and activation of downstream signaling molecules were determined using Western blotting. Results: PLCG1 and PLCG2 mRNA expression was significantly higher in GO orbital tissues than in controls (P<0.05). PLCG1 and PLCG2 mRNA expression was significantly increased (P<0.05) in IL-1β, tumor necrosis factor-α, and a cluster of differentiation 40 ligand-stimulated GO fibroblasts. U73122 significantly inhibited the IL-1β-induced expression of proinflammatory molecules, including IL-6, IL-8, monocyte chemoattractant protein-1, cyclooxygenase-2, and intercellular adhesion molecule-1 (ICAM-1), and phosphorylated protein kinase B (p-Akt) and p38 (p-p38) kinase in GO fibroblasts, whereas it inhibited IL-6, IL-8, and ICAM-1, and p-Akt and c-Jun N-terminal kinase (p-JNK) in normal fibroblasts (P<0.05). Conclusion PLC-γ-inhibiting U73122 suppressed the production of proinflammatory cytokines and the phosphorylation of Akt and p38 kinase in GO fibroblasts. This study indicates the implications of PLC-γ in GO pathogenesis and its potential as a therapeutic target for GO.

Background: The Korea National Antimicrobial Use Analysis System (KONAS), a benchmarking system for antimicrobial use in hospitals, provides Korean Standardized Antimicrobial Administration Ratio (K-SAAR) for benchmarking. This article describes K-SAAR predictive models to enhance the understanding of K-SAAR, an important benchmarking strategy for antimicrobial usage in KONAS. Methods: We obtained medical insurance claims data for all hospitalized patients aged ≥ 28 days in all secondary and tertiary care hospitals in South Korea (n = 347) from January 2019 to December 2019 from the Health Insurance Review & Assessment Service. Modeling was performed to derive a prediction value for antimicrobial use in each institution, which corresponded to the denominator value for calculating K-SAAR. The prediction values of antimicrobial use were modeled separately for each category, for all inpatients and adult patients (aged ≥ 15 years), using stepwise negative binomial regression. Results: The final models for each antimicrobial category were adjusted for different significant risk factors. In the K-SAAR models of all aged patients as well as adult patients, most antimicrobial categories included the number of hospital beds and the number of operations as significant factors, while some antimicrobial categories included mean age for inpatients, hospital type, and the number of patients transferred from other hospitals as significant factors. Conclusion We developed a model to predict antimicrobial use rates in Korean hospitals, and the model was used as the denominator of the K-SAAR.

Background: Angiotensin-converting enzyme 2 (ACE2) and transmembrane protease serine subtype 2 (TMPRSS2) are key proteins mediating viral entry of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Although gene expressions of ACE2 and TMPRSS2 have been analyzed in various organs and diseases, their soluble forms have been less studied, particularly in asthma. Therefore, we aimed to measure circulating ACE2 and TMPRSS2 in the serum of asthmatics and examine their relationship with clinical characteristics. Methods: Clinical data and serum samples of 400 participants were obtained from an asthma cohort. The soluble ACE2 (sACE2) and soluble TMPRSS2 (sTMPRSS2) level was measured by enzyme-linked immunosorbent assay, and the values underwent a natural log transformation. Associations between sACE2 and TMPRSS2 levels and various clinical variables were analyzed. Results: The patients younger than 70 years old, those with eosinophilic asthma (eosinophils ≥ 200 cells/µL), and inhaled corticosteroids (ICS) non-users were associated with higher levels of sACE2. Blood eosinophils and fractionated exhaled nitric oxide levels were positively correlated with serum ACE2. In contrast, lower levels of sTMPRSS2 were noted in patients below 70 years and those with eosinophilic asthma, while no association was noted between ICS use and sTMPRSS2. The level of sTMPRSS2 also differed according to sex, smoking history, coexisting hypertension, and forced expiratory volume in 1 second/forced vital capacity (FEV1/FVC) ratio. The proportion of sputum neutrophils was positively correlated with sTMPRSS2, while the FEV1/FVC ratio reported a negative correlation with sTMPRSS2. Conclusion The levels of ACE2 and TMPRSS2 were differently expressed according to age, ICS use, and several inflammatory markers. These findings suggest variable susceptibility and prognosis of SARS-CoV-2 infection among asthmatic patients.

The diagnostic and treatment methods of multiple myeloma (MM) have been rapidly evolving owing to advances in imaging techniques and new therapeutic agents. Imaging has begun to play an important role in the management of MM, and international guidelines are frequently updated. Since the publication of 2015 International Myeloma Working Group (IMWG) criteria for the diagnosis of MM, whole-body magnetic resonance imaging (MRI) or low-dose whole-body computed tomography (CT) and 18F-fluorodeoxyglucose positron emission tomography/CT have entered the mainstream as diagnostic and treatment response assessment tools. The 2019 IMWG guidelines also provide imaging recommendations for various clinical settings. Accordingly, radiologists have become a key component of MM management. In this review, we provide an overview of updates in the MM field with an emphasis on imaging modalities.