Background: Single room isolation with contact precautions is widely regarded as a fundamental strategy to prevent the transmission of multidrug-resistant organisms (MDROs). However, its implementation demands substantial resources, limiting its universal application to all MDROs. In this study, we assessed the effect of discontinuing single room isolation for vancomycin-resistant Enterococcus (VRE). Methods: This is a retrospective, observational study conducted at a single 750-bed tertiary center. We conducted an interrupted time series analysis to compare incidence rates and trends of new-onset VRE colonization and bacteremia during the one year before and after the strategy change on January 1, 2023. Results: Single-room occupancy decreased from 79.7% pre-intervention to 23.6% postintervention (P < 0.001). The incidence rate of new-onset VRE colonization was 0.452 and 0.535 per 1,000 patient-days in the pre- and post-intervention periods, respectively, with no statistically significant difference (P = 0.202). However, there was a slightly increasing trend (0.036 [95% confidence interval, −0.002, 0.074] increase per month, P = 0.066). The new-onset VRE bacteremia incidence rate was not differed in incidence (0.060 and 0.055, P= 0.571) or trend (P = 0.720). Conclusion Our study suggests that discontinuing single-room isolation for VRE patients may not affect the incidence of new-onset VRE bacteremia, but caution is needed due to the potential increase in colonization.

Background: Single room isolation with contact precautions is widely regarded as a fundamental strategy to prevent the transmission of multidrug-resistant organisms (MDROs). However, its implementation demands substantial resources, limiting its universal application to all MDROs. In this study, we assessed the effect of discontinuing single room isolation for vancomycin-resistant Enterococcus (VRE). Methods: This is a retrospective, observational study conducted at a single 750-bed tertiary center. We conducted an interrupted time series analysis to compare incidence rates and trends of new-onset VRE colonization and bacteremia during the one year before and after the strategy change on January 1, 2023. Results: Single-room occupancy decreased from 79.7% pre-intervention to 23.6% postintervention (P < 0.001). The incidence rate of new-onset VRE colonization was 0.452 and 0.535 per 1,000 patient-days in the pre- and post-intervention periods, respectively, with no statistically significant difference (P = 0.202). However, there was a slightly increasing trend (0.036 [95% confidence interval, −0.002, 0.074] increase per month, P = 0.066). The new-onset VRE bacteremia incidence rate was not differed in incidence (0.060 and 0.055, P= 0.571) or trend (P = 0.720). Conclusion Our study suggests that discontinuing single-room isolation for VRE patients may not affect the incidence of new-onset VRE bacteremia, but caution is needed due to the potential increase in colonization.

Background: Single room isolation with contact precautions is widely regarded as a fundamental strategy to prevent the transmission of multidrug-resistant organisms (MDROs). However, its implementation demands substantial resources, limiting its universal application to all MDROs. In this study, we assessed the effect of discontinuing single room isolation for vancomycin-resistant Enterococcus (VRE). Methods: This is a retrospective, observational study conducted at a single 750-bed tertiary center. We conducted an interrupted time series analysis to compare incidence rates and trends of new-onset VRE colonization and bacteremia during the one year before and after the strategy change on January 1, 2023. Results: Single-room occupancy decreased from 79.7% pre-intervention to 23.6% postintervention (P < 0.001). The incidence rate of new-onset VRE colonization was 0.452 and 0.535 per 1,000 patient-days in the pre- and post-intervention periods, respectively, with no statistically significant difference (P = 0.202). However, there was a slightly increasing trend (0.036 [95% confidence interval, −0.002, 0.074] increase per month, P = 0.066). The new-onset VRE bacteremia incidence rate was not differed in incidence (0.060 and 0.055, P= 0.571) or trend (P = 0.720). Conclusion Our study suggests that discontinuing single-room isolation for VRE patients may not affect the incidence of new-onset VRE bacteremia, but caution is needed due to the potential increase in colonization.

Background: Single room isolation with contact precautions is widely regarded as a fundamental strategy to prevent the transmission of multidrug-resistant organisms (MDROs). However, its implementation demands substantial resources, limiting its universal application to all MDROs. In this study, we assessed the effect of discontinuing single room isolation for vancomycin-resistant Enterococcus (VRE). Methods: This is a retrospective, observational study conducted at a single 750-bed tertiary center. We conducted an interrupted time series analysis to compare incidence rates and trends of new-onset VRE colonization and bacteremia during the one year before and after the strategy change on January 1, 2023. Results: Single-room occupancy decreased from 79.7% pre-intervention to 23.6% postintervention (P < 0.001). The incidence rate of new-onset VRE colonization was 0.452 and 0.535 per 1,000 patient-days in the pre- and post-intervention periods, respectively, with no statistically significant difference (P = 0.202). However, there was a slightly increasing trend (0.036 [95% confidence interval, −0.002, 0.074] increase per month, P = 0.066). The new-onset VRE bacteremia incidence rate was not differed in incidence (0.060 and 0.055, P= 0.571) or trend (P = 0.720). Conclusion Our study suggests that discontinuing single-room isolation for VRE patients may not affect the incidence of new-onset VRE bacteremia, but caution is needed due to the potential increase in colonization.

Objectives: Skin cancer is a prevalent type of malignancy, necessitating efficient diagnostic tools. This study aimed to develop an automated skin lesion classification model using the dynamically expandable representation (DER) incremental learning algorithm. This algorithm adapts to new data and expands its classification capabilities, with the goal of creating a scalable and efficient system for diagnosing skin cancer. Methods: The DER model with incremental learning was applied to the HAM10000 and ISIC 2019 datasets. Validation involved two steps: initially, training and evaluating the HAM10000 dataset against a fixed ResNet-50; subsequently, performing external validation of the trained model using the ISIC 2019 dataset. The model’s performance was assessed using precision, recall, the F1-score, and area under the precision-recall curve. Results: The developed skin lesion classification model demonstrated high accuracy and reliability across various types of skin lesions, achieving a weighted-average precision, recall, and F1-score of 0.918, 0.808, and 0.847, respectively. The model’s discrimination performance was reflected in an average area under the curve (AUC) value of 0.943. Further external validation with the ISIC 2019 dataset confirmed the model’s effectiveness, as shown by an AUC of 0.911. Conclusions This study presents an optimized skin lesion classification model based on the DER algorithm, which shows high performance in disease classification with the potential to expand its classification range. The model demonstrated robust results in external validation, indicating its adaptability to new disease classes.

Objective: Early detection and intervention of developmental disabilities (DDs) are critical to improving the long-term outcomes of afflicted children. In this study, our objective was to utilize facial landmark features from mobile application to distinguish between children with DDs and typically developing (TD) children. Methods: The present study recruited 89 children, including 33 diagnosed with DD, and 56 TD children. The aim was to examine the effectiveness of a deep learning classification model using facial video collected from children through mobile-based application. The study participants underwent comprehensive developmental assessments, which included the child completion of the Korean Psychoeducational Profile-Revised and caregiver completing the Korean versions of Vineland Adaptive Behavior Scale, Korean version of the Childhood Autism Rating Scale, Social Responsiveness Scale, and Child Behavior Checklist. We extracted facial landmarks from recorded videos using mobile application and performed DDs classification using long short-term memory with stratified 5-fold cross-validation. Results: The classification model shows an average accuracy of 0.88 (range: 0.78–1.00), an average precision of 0.91 (range: 0.75–1.00), and an average F1-score of 0.80 (range: 0.60–1.00). Upon interpreting prediction results using SHapley Additive exPlanations (SHAP), we verified that the most crucial variable was the nodding head angle variable, with a median SHAP score of 2.6. All the top 10 contributing variables exhibited significant differences in distribution between children with DD and TD (p<0.05). Conclusion The results of this study provide evidence that facial landmarks, utilizing readily available mobile-based video data, can be used to detect DD at an early stage.

Objectives: The objective of this study was to develop and validate a multicenter-based, multi-model, time-series deep learning model for predicting drug-induced liver injury (DILI) in patients taking angiotensin receptor blockers (ARBs). The study leveraged a national-level multicenter approach, utilizing electronic health records (EHRs) from six hospitals in Korea. Methods: A retrospective cohort analysis was conducted using EHRs from six hospitals in Korea, comprising a total of 10,852 patients whose data were converted to the Common Data Model. The study assessed the incidence rate of DILI among patients taking ARBs and compared it to a control group. Temporal patterns of important variables were analyzed using an interpretable timeseries model. Results: The overall incidence rate of DILI among patients taking ARBs was found to be 1.09%. The incidence rates varied for each specific ARB drug and institution, with valsartan having the highest rate (1.24%) and olmesartan having the lowest rate (0.83%). The DILI prediction models showed varying performance, measured by the average area under the receiver operating characteristic curve, with telmisartan (0.93), losartan (0.92), and irbesartan (0.90) exhibiting higher classification performance. The aggregated attention scores from the models highlighted the importance of variables such as hematocrit, albumin, prothrombin time, and lymphocytes in predicting DILI. Conclusions Implementing a multicenter-based timeseries classification model provided evidence that could be valuable to clinicians regarding temporal patterns associated with DILI in ARB users. This information supports informed decisions regarding appropriate drug use and treatment strategies.

Background: Tea tree oil has antiviral, antimicrobial and antifungal effects and Mastic oil has antifungal and anticancer effects. For synergistic effects of oils, blending oil containing a mixture of two to three oils is recommended. This study aimed to determine the antibacterial effects of Tea tree oil, Mastic oil, and Blending oil containing the two oils in a mixture, to verify and suggest the potential use of these oils as a substance to prevent dental caries. Methods: Tea tree oil, Mastic oil, and Blending oil with a 1:1 blend of the two oils were diluted in liquid medium to 0% (negative control), 0.5%, 1.0%, and 2.0%. Streptococcus mutans was applied to each experimental group of the three diluted oils and after 8 h culture, the optical density (OD) was measured and the growth inhibition rate for S. mutans was estimated. Results: Tea tree oil had significantly low OD values across all concentrations (p<0.05) without significant variation among different concentrations (p>0.05). Mastic oil did not significantly vary in OD compared to the negative control across all concentrations (p>0.05) without significant variation among different concentrations (p>0.05). Blending oil, compared to the negative control, did not significantly vary in OD at 0.5% (p>0.05) but significant variation was found as the concentration increased (p<0.05). Additionally, for Tea tree oil and Mastic oil, the growth inhibition rate showed no significant variation according to concentration (p>0.05), whereas for Blending oil, the growth inhibition rate for S. mutans showed a significant difference at 1.0% (p<0.05) and at higher concentrations. Conclusion Blending oil containing a Tea tree oil and Mastic oil demonstrated a significant growth inhibition effect on S. mutans from the concentration of 1.0%, which suggested its potential use as an effective antibacterial agent for dental caries.

In this study, the Search Your Mind (S.Y.M., 心) project aimed to collect prospective digital phenotypic data centered on mood and anxiety symptoms across psychiatric disorders through a smartphone application (app) platform while using both centralized and decentralized research designs: the centralized research design is a hybrid of a general prospective observational study and a digital platform-based study, and it includes face-to-face research such as informed written consent, clinical evaluation, and blood sampling. It also includes digital phenotypic assessment through an application-based platform using wearable devices. Meanwhile, the decentralized research design is a non-face-to-face study in which anonymous participants agree to electronic informed consent forms on the app. It also exclusively uses an application-based platform to acquire individualized digital phenotypic data. We expect to collect clinical, biological, and digital phenotypic data centered on mood and anxiety symptoms, and we propose a possible model of centralized and decentralized research design.