Since the late 1990s, online e-learning has offered unparalleled convenience and affordability, becoming increasingly popular among pathologists. Traditional learning theories have been successfully applied to web/mobile-based learning systems, with mobile technologies even enhancing conventional offline education. In cytopathology, hands-on microscope training has traditionally been paramount, complemented by real-case presentations and lectures. However, the coronavirus disease 2019 (COVID-19) pandemic disrupted regular academic activities, making online e-learning platforms essential. We designed a web/mobile-based learning platform to enhance continued medical education in cytopathology at various levels, particularly during the era of COVID-19 and beyond. Since 2021, we have integrated curriculum materials, virtual education files, and whole-slide images (WSIs) of cytopathology, submitted from over 200 institutions across Korea, with the support of numerous instructors. We develop a new e-learning platform named “CytoAcademy” composed of a basic session for each organ and level across the range of morphologic findings; on-demand lectures to enhance cytopathologic knowledge; WSI archives that allow users to explore various histologically confirmed cases; and a self-assessment test to help organize diagnostic knowledge acquired through the web/mobile-friendly learning system. The platform provides not just an opportunity to achieve a correct diagnosis, but also a learning experience based on problem-solving point. Members interact, identify their deficiencies, and focus on specific educational materials. In this manner, all participants can actively engage in creating and maintaining knowledge and foster a proactive approach to learning.

Background: Many pregnant women receive antibiotic treatment for infections. We investigated the association between quinolone use in the first trimester of pregnancy and the risk of adverse health outcomes for the child in Korea. Materials and Methods: This nationwide, population-based cohort study used data on mother-child pairs from the National Health Insurance claims database. This study cohort included 2,177,765 pregnancies from January 1, 2011, to December 31, 2020, and 87,456 women were prescribed quinolones during pregnancy. After propensity score matching, the final number of study subjects was 84,365 for both quinolone and non-antibiotic users. We examined the subjects’ exposure to quinolone antibiotics. The main outcome measures were absolute and relative risks of atopic dermatitis, asthma, and allergies. We adjusted for potential confounders. Results: Quinolones were prescribed at least once during the first trimester in 4.01% of pregnancies. Quinolone users had significantly higher absolute risks than non-antibiotic users for atopic dermatitis, asthma, and allergies, with significantly elevated risk ratios (RRs) for these conditions (atopic dermatitis: RR, 1.09; 95% confidence interval [CI], 1.08–1.11, asthma: RR, 1.04; 95% CI, 1.03–1.05, and allergies: RR, 1.10; 95% CI, 1.08–1.13). Conclusion We found that quinolone exposure during the first trimester of pregnancy increased the risk of atopic dermatitis, asthma, and allergies. This study could provide physicians with useful information when selecting antibiotics for pregnant women.

Background: Many pregnant women receive antibiotic treatment for infections. We investigated the association between quinolone use in the first trimester of pregnancy and the risk of adverse health outcomes for the child in Korea. Materials and Methods: This nationwide, population-based cohort study used data on mother-child pairs from the National Health Insurance claims database. This study cohort included 2,177,765 pregnancies from January 1, 2011, to December 31, 2020, and 87,456 women were prescribed quinolones during pregnancy. After propensity score matching, the final number of study subjects was 84,365 for both quinolone and non-antibiotic users. We examined the subjects’ exposure to quinolone antibiotics. The main outcome measures were absolute and relative risks of atopic dermatitis, asthma, and allergies. We adjusted for potential confounders. Results: Quinolones were prescribed at least once during the first trimester in 4.01% of pregnancies. Quinolone users had significantly higher absolute risks than non-antibiotic users for atopic dermatitis, asthma, and allergies, with significantly elevated risk ratios (RRs) for these conditions (atopic dermatitis: RR, 1.09; 95% confidence interval [CI], 1.08–1.11, asthma: RR, 1.04; 95% CI, 1.03–1.05, and allergies: RR, 1.10; 95% CI, 1.08–1.13). Conclusion We found that quinolone exposure during the first trimester of pregnancy increased the risk of atopic dermatitis, asthma, and allergies. This study could provide physicians with useful information when selecting antibiotics for pregnant women.

Since the late 1990s, online e-learning has offered unparalleled convenience and affordability, becoming increasingly popular among pathologists. Traditional learning theories have been successfully applied to web/mobile-based learning systems, with mobile technologies even enhancing conventional offline education. In cytopathology, hands-on microscope training has traditionally been paramount, complemented by real-case presentations and lectures. However, the coronavirus disease 2019 (COVID-19) pandemic disrupted regular academic activities, making online e-learning platforms essential. We designed a web/mobile-based learning platform to enhance continued medical education in cytopathology at various levels, particularly during the era of COVID-19 and beyond. Since 2021, we have integrated curriculum materials, virtual education files, and whole-slide images (WSIs) of cytopathology, submitted from over 200 institutions across Korea, with the support of numerous instructors. We develop a new e-learning platform named “CytoAcademy” composed of a basic session for each organ and level across the range of morphologic findings; on-demand lectures to enhance cytopathologic knowledge; WSI archives that allow users to explore various histologically confirmed cases; and a self-assessment test to help organize diagnostic knowledge acquired through the web/mobile-friendly learning system. The platform provides not just an opportunity to achieve a correct diagnosis, but also a learning experience based on problem-solving point. Members interact, identify their deficiencies, and focus on specific educational materials. In this manner, all participants can actively engage in creating and maintaining knowledge and foster a proactive approach to learning.

Background: Many pregnant women receive antibiotic treatment for infections. We investigated the association between quinolone use in the first trimester of pregnancy and the risk of adverse health outcomes for the child in Korea. Materials and Methods: This nationwide, population-based cohort study used data on mother-child pairs from the National Health Insurance claims database. This study cohort included 2,177,765 pregnancies from January 1, 2011, to December 31, 2020, and 87,456 women were prescribed quinolones during pregnancy. After propensity score matching, the final number of study subjects was 84,365 for both quinolone and non-antibiotic users. We examined the subjects’ exposure to quinolone antibiotics. The main outcome measures were absolute and relative risks of atopic dermatitis, asthma, and allergies. We adjusted for potential confounders. Results: Quinolones were prescribed at least once during the first trimester in 4.01% of pregnancies. Quinolone users had significantly higher absolute risks than non-antibiotic users for atopic dermatitis, asthma, and allergies, with significantly elevated risk ratios (RRs) for these conditions (atopic dermatitis: RR, 1.09; 95% confidence interval [CI], 1.08–1.11, asthma: RR, 1.04; 95% CI, 1.03–1.05, and allergies: RR, 1.10; 95% CI, 1.08–1.13). Conclusion We found that quinolone exposure during the first trimester of pregnancy increased the risk of atopic dermatitis, asthma, and allergies. This study could provide physicians with useful information when selecting antibiotics for pregnant women.

Since the late 1990s, online e-learning has offered unparalleled convenience and affordability, becoming increasingly popular among pathologists. Traditional learning theories have been successfully applied to web/mobile-based learning systems, with mobile technologies even enhancing conventional offline education. In cytopathology, hands-on microscope training has traditionally been paramount, complemented by real-case presentations and lectures. However, the coronavirus disease 2019 (COVID-19) pandemic disrupted regular academic activities, making online e-learning platforms essential. We designed a web/mobile-based learning platform to enhance continued medical education in cytopathology at various levels, particularly during the era of COVID-19 and beyond. Since 2021, we have integrated curriculum materials, virtual education files, and whole-slide images (WSIs) of cytopathology, submitted from over 200 institutions across Korea, with the support of numerous instructors. We develop a new e-learning platform named “CytoAcademy” composed of a basic session for each organ and level across the range of morphologic findings; on-demand lectures to enhance cytopathologic knowledge; WSI archives that allow users to explore various histologically confirmed cases; and a self-assessment test to help organize diagnostic knowledge acquired through the web/mobile-friendly learning system. The platform provides not just an opportunity to achieve a correct diagnosis, but also a learning experience based on problem-solving point. Members interact, identify their deficiencies, and focus on specific educational materials. In this manner, all participants can actively engage in creating and maintaining knowledge and foster a proactive approach to learning.

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.