Purpose: This study aimed to examine the relationships between artificial intelligence (AI) knowledge, attitudes, perceptions, and utilization ability, and their influence on communication competence in nursing students. Methods: A descriptive cross-sectional study was conducted with 160 nursing students from three universities in Chungcheongbuk-do, Korea, between September 12 and 19, 2025. Data were collected using self-administered questionnaires to assess AI knowledge, attitudes, perception and utilization ability, and communication competence. Data were analyzed using descriptive statistics, independent t-tests, one-way ANOVA, Pearson’s correlation coefficients, and stepwise multiple regression using IBM SPSS version 26.0. Results: The mean scores for communication competence were 180.63±16.56. The scores for AI knowledge, positive attitudes, negative attitudes, and perception/utilization ability were 10.53±3.59, 45.06±4.44, 22.25±3.80, and 88.33±12.50, respectively. Significant predictors of communication competence included positive attitudes toward AI (B=0.95, p=.003), perceived ease of use (B=1.15, p=.009), and AI usage time of five hours or more per week (B=8.23, p=.015). These factors explained 22.0% of the variance in communication competence. Conclusion Educational interventions that foster positive attitudes toward AI, enhance perceived ease of use through user-friendly tools, and provide sufficient hands-on experience with AI programs may effectively improve nursing students’ communication competence.

Subarachnoid hemorrhage (SAH) is a stroke subtype with high mortality and poor functional outcomes. Prompt occlusion of a ruptured aneurysm at an early stage is crucial to prevent rebleeding, which can result in even higher mortality and more severe disabilities. The most critical initial decision in SAH management is the choice of treatment method with surgical clipping or endovascular coiling. We aimed to develop an evidence-based clinical guideline to select the optimal initial treatment in patients with SAH. We developed this guideline based on evidence from systematic reviews and meta-analyses via a de novo process. A systematic literature review was conducted across four databases (MEDLINE, Embase, Cochrane, and KoreaMed) to answer two population, intervention, comparison, outcome questions comparing clipping and coiling. The risk of bias was assessed using ROB 2.0 and the Newcastle-Ottawa Scale. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses flow diagrams and meta-analyses were generated for functional outcome and mortality. We included six randomized control trials (RCTs) and 58 observational studies. Meta-analysis of RCTs showed that coiling improved functional outcomes compared to clipping (odds ratio [OR], 0.91; 95% confidence interval [CI], 0.86–0.97). No significant mortality difference was observed in RCTs (OR, 1.38; 95% CI, 0.91–2.09), but non-RCTs favored clipping for reduced mortality (OR, 0.77; 95% CI, 0.69–0.86). However, it is difficult to generalize these findings to all clinical situations, as patients with SAH have a highly variable clinical course. Final treatment decision should be tailored to the individual patient’s status, including aneurysm location, morphology, and the expertise available at the treatment center. Such decisions are best made by specialists such as a board-certified physician and should be explained to the patient and their caregivers, along with the rationale for selecting the most appropriate treatment at the given hospital. Korea has many certified endovascular neurosurgeons, cerebrovascular surgeons, and certified cerebrovascular centers. Proper selection of the most suitable treatment method by certified physicians and centers would greatly benefit patient outcomes and healthcare professionals.

Accurate and early identification of stroke and large vessel occlusion (LVO) in emergency settings is essential for improving patient outcomes and ensuring the efficient allocation of medical resources. This clinical practice guideline systematically reviews domestic and international literature and conducts meta-analyses to evaluate the utility and diagnostic accuracy of stroke assessment tools used in prehospital emergency medical services (EMS). We developed a guideline based on evidence from systematic reviews and meta-analyses via a de novo process. A systematic literature review was conducted to evaluate the usefulness of diagnostic EMS assessment tools for diagnosing stroke and LVO. Overall, 70 non-randomized control studies were selected for this study. A meta-analysis was conducted with a subgroup analysis to distinguish between patients with stroke and those with LVO. EMS tools demonstrated high sensitivity but low specificity for diagnosing stroke. In the prehospital setting, using validated EMS stroke assessment tools is recommended for the early identification of stroke and LVO. Upon hospital arrival, stroke specialists should conduct further evaluation and triage to confirm the diagnosis and guide appropriate management. Delays in diagnosing LVO are frequently unacceptable. While experts advocate for the use of EMS assessment tools to facilitate early identification of LVO, these tools alone lack adequate sensitivity. Therefore, further diagnostic evaluations and consultation with stroke specialists upon hospital arrival are recommended.

The mothership (MS) model, where patients are directly transferred to a thrombectomy-capable center, and the drip-and-ship (DS) model, where thrombolysis is initiated at the nearest primary stroke center before transfer for thrombectomy, are the primary transport modes for patients with stroke. We aimed to establish guidelines for selecting the appropriate transfer strategy based on emergent large vessel occlusion (LVO). We developed this guideline based on evidence from systematic reviews and meta-analyses via a de novo process. A systematic literature review was conducted across four databases (MEDLINE, Embase, Cochrane, and KoreaMed) to answer three Population, Intervention, Comparison, and Outcome questions comparing MS and DS models. The risk of bias was assessed using the Newcastle-Ottawa Scale. Preferred Reporting Items for Systematic Reviews and Meta-Analyses flow diagrams and meta-analyses were generated for functional outcomes, mortality, and successful recanalization. Twenty-six non-randomized controlled studies showed that the MS model improved good functional outcomes by approximately 14% compared with the DS model (odds ratio [OR], 1.14; 95% confidence interval [CI], 1.00–1.30). Fifteen studies reported that mortality in the MS and DS models showed no significant differences (OR, 0.97; 95% CI, 0.84–1.11). Twenty-four studies revealed no significant difference in successful recanalization between the MS and DS models (OR, 0.87; 95% CI, 0.68–1.10). The MS model should be considered first to improve the functional outcome of patients with LVO. However, if thrombectomy cannot be performed immediately after thrombolysis, or if a thrombectomy-enabled hospital is not nearby, the DS model should be considered by stroke specialists depending on transportation time and regional factors. We suggest a mixed approach with the DS model based on specific circumstances or regions to ensure the optimum treatment of patients with acute ischemic stroke (AIS). Appropriate transport for patients with LVO improves the prognosis of AIS.

Background: To investigate the fracture risks associated with anti-diabetic drugs in older women with type 2 diabetes mellitus (T2DM), who are particularly susceptible to skeletal fragility. Methods: Using data from the Korean National Health Insurance Service, this nested case-control study included 10,104 older women with T2DM and osteoporotic fractures (aged 66.5±3.4 years) matched in a 1:3 ratio with controls by birthdate, Charlson Comorbidity Index, and cohort entry date. We analyzed the odds of major osteoporotic fracture (MOF), vertebral fracture (VF), and non-VF (NVF) in users of sulfonylurea, thiazolidinedione (TZD), dipeptidyl peptidase-4 inhibitor, and sodium-glucose cotransporter 2 inhibitor (SGLT2i), compared to metformin (Met)-only users using multivariable logistic regression. Results: During a follow-up period of 3.8±2.8 years, TZD users had a higher risk of MOF than Met-only users (odds ratio [OR], 1.35; 95% confidence interval [CI], 1.19-1.53; P<0.001). Risks of VF and NVF were also increased in the TZD group (OR, 1.21; 95% CI 1.03-1.42; P=0.022 and OR, 1.32; 95% CI 1.14-1.52; P<0.001, respectively). No significant differences were observed in other drug groups. The increased risk of VF and NVF in the TZD group were particularly pronounced in patients with normal or osteopenic bone mineral density (BMD) and in those with normal body mass index (BMI), respectively. Conclusions In older women with T2DM, TZD use was associated with increased VF and NVF risks, particularly among those with normal or osteopenic BMD and normal BMI. SGLT2i showed no increased risk, but further large-scale studies are needed to confirm its skeletal safety.

Natural killer (NK) cells are pivotal innate immune system components that exhibit spontaneous cytolytic activity against abnormal cells, such as infected and tumor cells. NK cells have shown significant promise in adoptive cell therapy because of their favorable safety profiles and minimal toxicity in clinical settings. Despite their advantages, the therapeutic application of unmodified NK cells faces challenges, including limited in vivo persistence, particularly in the immunosuppressive tumor microenvironment. Recent advances in genetic engineering have enhanced the therapeutic potential of NK cells by addressing these limitations and improving their therapeutic efficacy. In this review, we have described various methodologies for the genetic modification of NK cells, including viral vectors, electroporation, and nanoparticle-based approaches. The ongoing research on nanomaterialbased approaches highlights their potential to overcome current limitations in NK cell therapy, paving the way for advanced cancer therapy and improved clinical outcomes. In this review, we also emphasize the potential of engineered NK cells in cancer immunotherapy and other clinical applications, highlighting the expanding scope of NK cell-based treatments and the critical role of innovative genetic engineering techniques.

Background: Liver transplantation (LT) is the standard treatment for end-stage liver disease; however, it can lead to biliary strictures in 25%–30% of cases. We aimed to develop a biodegradable stent loaded with paclitaxel that could be inserted during surgery without requiring removal. We evaluated the safety and efficacy of this stent using a porcine model. Methods: Fourteen pigs underwent simulated ischemic injury during LT, and a biodegradable paclitaxel-eluting stent was inserted after duct-to-duct anastomosis.Pigs were divided into four groups: no stent (n=3), bare stent (n=3), 300 µg paclitaxel stent (n=4), and 900 µg paclitaxel stent (n=4). After 3 months of follow-up, autopsies were conducted to obtain common bile duct tissue samples, and inflammation and fibrosis thicknesses were assessed under a microscope. Results: Most tissues had resolved the inflammatory reactions by the 3-month mark. The thinnest fibrosis thickness was observed in the 900 µg group (359.08±167.23 µm); however, no statistical significance was observed. Conclusion This study demonstrated the safety of paclitaxel-eluting biodegradable biliary stents and their positive effects on fibrosis in an ischemic bile duct porcine model. This biodegradable stent represents a potential approach for overcoming the complications associated with biliary strictures after LT.

Breast MRI is the most sensitive imaging modality for detecting breast cancer. However, its widespread use is limited by factors such as extended examination times, need for contrast agents, and susceptibility to motion artifacts. Artificial intelligence (AI) has emerged as a promising solution for these challenges by enhancing the efficiency and accuracy of breast MRI in multiple domains. AI-driven image reconstruction techniques have significantly reduced scan times while preserving image quality. This method outperforms traditional parallel imaging and compressed sensing. AI has also shown great promise for lesion classification and segmentation, with convolutional neural networks and U-Net architectures improving the differentiation between benign and malignant lesions. AI-based segmentation methods enable accurate tumor detection and characterization, thereby aiding personalized treatment planning. An AI triaging system has demonstrated the potential to streamline workflow efficiency by identifying low-suspicion cases and reducing the workload of radiologists. Another promising application is synthetic breast MR image generation, which aims to generate contrast enhanced images from non-contrast sequences, thereby improving accessibility and patient safety. Further research is required to validate AI models across diverse populations and imaging protocols. As AI continues to evolve, it is expected to play an important role in the optimization of breast MRI.