Purpose: This study aimed to develop and evaluate the effectiveness of the Trauma-nursing Education and Skill Support (TESS) program based on the ADDIE model (Analysis, Design, Development, Implementation, Evaluation model). The program was designed to enhance trauma nurses’ clinical competencies, including trauma-related knowledge, self-efficacy, and problem-solving ability, through the integration of theoretical education and simulation-based practice. Methods: A quasi-experimental study using a non-equivalent control group pretest–posttest design was conducted. Participants included 108 trauma nurses from regional trauma centers, military trauma centers, and emergency care facilities, who were assigned to an experimental group (n=52) or a control group (n=56). The TESS program consisted of a 2-day, 14-hour blended-learning course that included eight lecture sessions and four simulation-based practice stations. Data were collected at baseline, immediately after the intervention, and at 6 months using validated instruments measuring trauma-related knowledge, self-efficacy, and problem-solving ability. Two-way repeated-measures analysis of variance was used for data analysis. Results: The experimental group demonstrated significant improvements in trauma-related knowledge, self-efficacy, and problem-solving ability compared with baseline (all p<.001). These improvements were sustained at 6 months, although trauma-related knowledge scores showed a slight decline compared with immediate posttest levels. Between-group analyses confirmed significant group-by-time interaction effects for all outcomes: trauma-related knowledge (η2=0.12, p<.001), self-efficacy (η2=0.09, p=.002), and problem-solving ability (η2=0.08, p=.003). Conclusion The TESS program effectively enhanced trauma nurses’ trauma-related knowledge, self-efficacy, and problem-solving ability, with effects sustained for up to 6 months. Incorporating blended learning and simulation-based training into standardized trauma nursing education may strengthen clinical competencies and ultimately contribute to improved patient outcomes.

Background: and Purpose: Tailored physical exercise interventions have the potential to promote cognitive health in older adults and offer significant advantages for those more vulnerable to decline. The specific relationship between physical fitness and cognition among the elderly has not been clearly established. The purpose of this investigation was to assess the relationship between physical fitness and cognitive function in older Korean adults. Methods: Eighty-four community-dwelling older adults (mean age: 70.7±5.3 years; 81.0% female) completed a standardized physical fitness battery assessing handgrip strength, sit-and-reach, 30-second sit-to-stand, 2-minute stationary march, 3-m sit-walk-and-return, figure-8-walk, and T-wall response time. Cognitive function was evaluated using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). Descriptive statistics, partial correlation analyses, and stepwise multiple linear regression were conducted. Results: Slower T-wall response time was significantly correlated with lower RBANS total index, immediate memory, and delayed memory scores. In regression models, slower T-wall response time was independently associated with lower RBANS total index (β=−0.234, p=0.026) and delayed memory scores (β=−0.295, p=0.029). The regression model for immediate memory was not statistically significant overall; therefore, no predictive conclusion was drawn for this domain. Higher education showed a significant positive association with cognitive performance. Conclusions Coordination, as measured by T-wall response time, emerged as the only physical fitness component consistently associated with cognitive performance in older adults. Coordination-related fitness may be an important correlate of cognitive function in older adults and a promising target for future exercise interventions.

Background/Aims: Recent advances in computer-aided diagnosis (CADx) systems have demonstrated expert-level accuracy in the optical diagnosis of colorectal polyps. High-confidence (HC) diagnoses have been defined as those made within 3 seconds without hesitation, and these systems have been shown to improve diagnostic accuracy. We aimed to evaluate the performance of endoscopists with varying levels of experience in diagnosing colorectal polyps with the assistance of a new CADx system applying the 3-second rule and without artificial intelligence assistance. Methods: In this multicenter ex vivo study, 35 endoscopists assessed 100 polyps (51 adenomas, 39 hyperplastic polyps, 10 sessile serrated lesions) using narrow-band imaging video clips on an online platform. Assessments consisted of individual endoscopist diagnosis and CADx-assisted diagnosis. HC assignments followed the 3-second rule in both phases. Performance metrics included HC accuracy, HC rate, and adherence to the Preservation and Incorporation of Valuable Endoscopic Innovations (PIVI) and Simple Optical Diagnosis Accuracy (SODA) thresholds. Results: HC diagnostic accuracy improved from 78.3% (95% confidence interval [CI], 76.6% to 80.0%) to 89.8% (95% CI, 88.6% to 90.9%) with CADx assistance (p<0.001). The proportion of HC predictions increased from 64.2% to 75.4% (p<0.001). Novice endoscopists showed marked improvement with CADx (74.1% vs 88.8%; p<0.001). CADx-assisted diagnoses nearly met SODA and PIVI thresholds under the 3-second rule. Additional analysis demonstrated that CADx assistance significantly improved interobserver agreement and ground truth, particularly for novices (κ=0.37 to κ=0.65; p<0.001). Conclusions Integrating CADx with the 3-second rule significantly enhances the performance of endoscopists in the optical diagnosis of colorectal polyps, with the greatest benefit observed among novice endoscopists.

Objective: Research specifically targeting suicidal ideation (SI) in middle-aged populations remains limited. This study aimed to predict future and concurrent SI in middle-aged Korean adults by applying four machine learning (ML) models to a nationally representative longitudinal dataset. Methods: We analyzed data from 8,992 individuals aged 40–64 years who participated in the Korea Welfare Panel Study from the 7th (2011) to the 18th (2022) waves. Four ML algorithms were employed to develop the predictive models. The SHapley Additive exPlanations method was applied to enhance explainability. Results: Approximately half of the participants’ mean age was 49.3±8.2 years (range, 40–64 years) and 52.2% were male. The average annual SI rate between 2011 and 2022 was 2.8%±1.2%. Predictive performance for future SI was satisfactory, with area under the receiver operating characteristic curve (AUC) values of up to 0.806 (logistic regression, LR). Predictions for concurrent SI demonstrated AUC values of up to 0.907 (LR). Key predictors of future SI included subjective health status, satisfaction with family and spousal relationships, housing environment, and educational attainment. Concurrent SI was strongly associated with immediate stressors such as family violence and income dissatisfaction. Conclusion The ML models demonstrated good-to-excellent predictive performance for SI. These findings emphasize the importance of health, family, and socioeconomic factors, alongside mental health indicators in the prevention of SI among middle-aged adults. Building on these findings, tailored intervention strategies that comprehensively address multidimensional risk factors are essential for effective SI prevention.

The common data model (CDM) has found widespread application in healthcare studies, but its utilization in cancer research has been limited. This article describes the development and implementation strategy for Cancer Clinical Library Databases (CCLDs), which are standardized cancer-specific databases established under the Korea-Clinical Data Utilization Network for Research Excellence (K-CURE) project by the Korean Ministry of Health and Welfare. Fifteen leading hospitals and fourteen academic associations in Korea are engaged in constructing CCLDs for 10 primary cancer types. For each cancer type-specific CCLD, cancer data experts determine key clinical data items essential for cancer research, standardize these items across cancer types, and create a standardized schema. Comprehensive clinical records covering diagnosis, treatment, and outcomes, with annual updates, are collected for each cancer patient in the target population, and quality control is based on six-sigma standards. To protect patient privacy, CCLDs follow stringent data security guidelines by pseudonymizing personal identification information and operating within a closed analysis environment. Researchers can apply for access to CCLD data through the K-CURE portal, which is subject to Institutional Review Board and Data Review Board approval. The CCLD is considered a pioneering standardized cancer-specific database, significantly representing Korea’s cancer data. It is expected to overcome limitations of previous CDMs and provide a valuable resource for multicenter cancer research in Korea.

The common data model (CDM) has found widespread application in healthcare studies, but its utilization in cancer research has been limited. This article describes the development and implementation strategy for Cancer Clinical Library Databases (CCLDs), which are standardized cancer-specific databases established under the Korea-Clinical Data Utilization Network for Research Excellence (K-CURE) project by the Korean Ministry of Health and Welfare. Fifteen leading hospitals and fourteen academic associations in Korea are engaged in constructing CCLDs for 10 primary cancer types. For each cancer type-specific CCLD, cancer data experts determine key clinical data items essential for cancer research, standardize these items across cancer types, and create a standardized schema. Comprehensive clinical records covering diagnosis, treatment, and outcomes, with annual updates, are collected for each cancer patient in the target population, and quality control is based on six-sigma standards. To protect patient privacy, CCLDs follow stringent data security guidelines by pseudonymizing personal identification information and operating within a closed analysis environment. Researchers can apply for access to CCLD data through the K-CURE portal, which is subject to Institutional Review Board and Data Review Board approval. The CCLD is considered a pioneering standardized cancer-specific database, significantly representing Korea’s cancer data. It is expected to overcome limitations of previous CDMs and provide a valuable resource for multicenter cancer research in Korea.

The common data model (CDM) has found widespread application in healthcare studies, but its utilization in cancer research has been limited. This article describes the development and implementation strategy for Cancer Clinical Library Databases (CCLDs), which are standardized cancer-specific databases established under the Korea-Clinical Data Utilization Network for Research Excellence (K-CURE) project by the Korean Ministry of Health and Welfare. Fifteen leading hospitals and fourteen academic associations in Korea are engaged in constructing CCLDs for 10 primary cancer types. For each cancer type-specific CCLD, cancer data experts determine key clinical data items essential for cancer research, standardize these items across cancer types, and create a standardized schema. Comprehensive clinical records covering diagnosis, treatment, and outcomes, with annual updates, are collected for each cancer patient in the target population, and quality control is based on six-sigma standards. To protect patient privacy, CCLDs follow stringent data security guidelines by pseudonymizing personal identification information and operating within a closed analysis environment. Researchers can apply for access to CCLD data through the K-CURE portal, which is subject to Institutional Review Board and Data Review Board approval. The CCLD is considered a pioneering standardized cancer-specific database, significantly representing Korea’s cancer data. It is expected to overcome limitations of previous CDMs and provide a valuable resource for multicenter cancer research in Korea.

Objective: As the coronavirus disease 2019 (COVID-19) pandemic has been prolonged, the pre-hospital screening test performed in hospitals has changed from polymerase chain reaction (PCR) to rapid antigen test (RAT). RAT has lower sensitivity than PCR, but a lower cost and shorter test time. In the hospital where this study was conducted, the preadmission COVID-19 test was changed from PCR to RAT on February 24, 2023. This study compared the efficacy of PCR and RAT as the pre-admission COVID-19 test. Methods: This was a retrospective observational study comparing two periods, 90 days from November 25, 2022 to February 23, 2023, and 90 days from February 28, 2023 to May 29, 2023. Patients hospitalized from the emergency medical center during these two periods were included. Binomial logistic regression was used to compare the emergency department length of stay (ED LOS) between the two groups (PCR vs. RAT). Logistic regression was used to compare the mortality. Results: Four thousand seven hundred and thirty-eight patients were admitted through the emergency room: 2,202 patients in the PCR group and 2,443 patients in the RAT group. No statistically significant differences in the characteristics and severity were observed between the two groups. The mean ED LOS of PCR 5.07 hours (interquartile range, 3.80-6.75) was longer than RAT 3.65 hours (interquartile range, 2.83-4.68) (P<0.001). Mortality was higher in PCR 8.9% than RAT 6.6% (P=0.005). Conclusion The study showed that ED LOS and mortality were reduced when using RAT rather than PCR as a preadmission COVID-19 test.

OBJECTIVES: This study investigated the associations between several obesity-related anthropometric indices and mortality in middle-aged and elderly populations to compare the indices’ predictive ability with that of the body mass index (BMI). METHODS: We analyzed data on 12 indices calculated from 19,805 community-based cohort participants (average age, 63.27 years; median follow-up, 13.49 years). Each index was calculated using directly measured values of height, weight, waist circumference (WC), and hip circumference (HC). We calculated hazard ratios (HRs) and 95% confidence intervals (CIs) for each index using Cox regression and evaluated mortality prediction with the Harrell concordance index (c-index). RESULTS: Adding anthropometric indices to the basic mortality model (c-index, 0.7723; 95% CI, 0.7647 to 0.7799) significantly increased the predictive power of BMI (c-index, 0.7735; 95% CI, 0.7659 to 0.7811), a body shape index (ABSI; c-index, 0.7735; 95% CI, 0.7659 to 0.7810), weight-adjusted waist index (WWI; c-index, 0.7731; 95% CI, 0.7656 to 0.7807), and waist to hip index (WHI; c-index, 0.7733; 95% CI, 0.7657 to 0.7809). The differences between the BMI model and the other 3 models were not statistically significant. CONCLUSIONS In predicting all-cause mortality, the ABSI, WWI, and WHI models based on WC or HC had stronger predictive power than conventional risk factors but were not significantly different from the BMI model.

Background: The purpose of this study was to detect signals of adverse events (AEs) of DPP-IV inhibitors using the KIDs-Korea Adverse Event Reporting System (KAERS) database. Methods: This study was conducted using AEs reported from January 2009to December 2018 in the KIDs-KAERS database. For signal detection, disproportionality analysis was performed. Signals of DPPIV inhibitor that satisfied the data-mining indices of reporting odds ratio (ROR) were detected. Results: Among the total number of 10,364 AEs to all oral hypoglycemic agents, the number of reported AEs related to DPP-IV inhibitors was 1,674. Analysis of re-ported AEs of DPP-IV inhibitors at the SOC levels showed that Respiratory system disorders were the highest at 4.31 (95% CI 3.01-6.17), followed by Skin and appendages disorders at 2.04 (95% CI 1.74-2.38). When analyzing AEs reported at the PT level, phar-yngitis was the highest at 73.90 (95% CI 17.59-310.49), followed by arthralgia at 6.08 (95% CI 2.04-18.11), and coughing at 5.21 (95% CI 2.07-13.15). Conclusions Based on the result of the study, deeper consideration is required according to the characteristics of the patients in prescribing DPP-IV inhibitors among oral hypoglycemic agents, and continuous monitoring of the occurrence of related Adverse Drug Reactions during administration is also required.