Background: The Ascertain Dementia 8-item Questionnaire (AD8) is a validated informant-based interview for early dementia detection. Research suggests the utility of self-rated AD8 to identify milder dementia forms in research settings. This study compares the factor structure, reliability, and diagnostic performance between AD8-Self and AD8-Informant for early cognitive impairment (ECI) in a clinical setting. Methods: Five hundreds fifteen patient-informant dyads (43 cognitively intact and 472 ECI) from a tertiary memory clinic completed both self-reported and informant AD8. We conducted exploratory factor analysis to determine the factor structure, Cronbach’s alpha for internal consistency, and receiver operating characteristic (ROC) curve analysis for ECI, including a subgroup analysis for mild cognitive impairment (MCI). Results: The mean age and education of ECI participants were 75.61 years (range, 51–95) and 5.6 years (range, 0–20), respectively, and 72.6 years (range, 51–89) and 6.8 years (range, 0–16) in the MCI subgroup. Unlike AD8-Informant’s one-factor structure, AD8-Self had a two-factor structure corresponding to memory and non-memory domains. AD8-Self demonstrated lower reliability (Cronbach’s alpha: ECI 0.666 vs. 0.764; MCI 0.663 vs. 0.709). In ECI, AD8-Informant (cutoff score ≥3) showed better diagnostic performance (sensitivity 89%, specificity 79%) than AD8-Self (cutoff score ≥4; sensitivity 27.1%, specificity 95.3%) (AUC 0.915 vs. 0.593; p<0.001). Similar results were found in MCI (sensitivity 64.7% vs. 26.5%; specificity 79.1% vs. 95.3%; AUC 0.745 vs. 0.600; p=0.002). Conclusion AD8-Self has a distinct factor structure, lower reliability, and inferior diagnostic performance compared to AD8-Informant for ECI/MCI detection. Our result do not support AD8-Self as a standalone tool for detecting ECI or MCI.

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.

Purpose: This study aimed to explore the practices, perceptions, and barriers related to specialty palliative care (SPC) referrals among oncologists in Korea, highlighting the clinical implications of early integration. Materials and Methods: A cross-sectional online survey targeting board-certified hemato-oncology specialists was conducted between August 1-25, 2024. The survey assessed referral practices, attitudes toward early SPC integration, referral criteria, barriers, and institutional characteristics. Results: A total of 227 oncologists participated (response rate, 36.7%). Among them, 68.7% reported frequent SPC referrals, with higher referral rates observed among younger physicians, those in tertiary hospitals, and institutions with in-house SPC teams (p < 0.001). Although 74.9% supported early SPC integration, referrals were often inconsistently timed, frequently occurring after disease progression or at the discontinuation of chemotherapy. For time-based referrals, the most commonly endorsed triggers were disease progression despite palliative second-line treatment and a prognosis of expected mortality within 6-12 months. Need-based referral triggers such as patient or family requests (96.5%), psychological distress (89.9%), or uncontrolled symptoms (83.3%), were also widely endorsed. The major barriers to early SPC integration included patient and family resistance (70.0%) and limited availability of SPC teams (34.4%). Conclusion This study emphasizes the importance of systematic efforts to promote timely SPC integration in Korea, including education to raise patient awareness, improved referral systems, and enhanced infrastructure. The positive attitudes toward early SPC among oncologists reflect a growing recognition of its value, highlighting the need for strategies that align with international standards.

Objective: This study aimed to compare aneuploidy rates and clinical outcomes between trophectoderm biopsy at fresh blastocyst (biopsy-fresh) followed by vitrification and biopsy at vitrified-warmed blastocyst (biopsy-vitri) followed by next day transfer (without re-vitrification). Methods: This retrospective study included 844 patients undergoing 844 cycles conducted from August 2019 to December 2023. Preimplantation genetic testing for aneuploidy (PGT-A) was performed via trophectoderm biopsy using array comparative genomic hybridization or next-generation sequencing for comprehensive 24-chromosome screening. Patients were divided into two groups based on the blastocyst status at the time of biopsy: the biopsy-fresh group (531 patients) and the biopsy-vitri group (313 patients). Results: The clinical pregnancy rate was significantly higher in the biopsy-fresh group compared to the biopsy-vitri group (58.7% vs. 45.6%; odds ratio [OR], 1.695; 95% confidence interval [CI], 1.215 to 2.364; p=0.002). Furthermore, the biopsy-fresh group showed higher implantation rates (45.6% vs. 32.1%; OR, 1.767; 95% CI, 1.274 to 2.451; p=0.002), ongoing pregnancy or live birth rates per cycle (48.0% vs. 35.8%; OR, 1.652; 95% CI, 1.177 to 2.319; p=0.004), and rates of good-quality blastocysts (57.1% vs. 32.1%, p<0.001) compared with the biopsy-vitri group. Miscarriage rates did not differ significantly between the groups (18.2% vs. 21.4%; OR, 0.818; 95% CI, 0.457 to 1.465; p=0.501). Conclusion Biopsy at fresh blastocyst demonstrated superior clinical outcomes compared with biopsy at vitrified-warmed blastocyst, likely due to better embryo quality. Both biopsy at fresh blastocyst and vitrified-warmed blastocyst remain viable options for PGT-A, with biopsy at vitrified-warmed blastocyst serving as a practical alternative. Embryo quality and euploid status continue to be critical considerations for embryo transfer selection.

In patients with differentiated thyroid cancer (DTC), initial recurrence risk stratification based on clinical, histopathological, and perioperative data remains the key determinant for guiding management strategies during the first 1-2 years post-treatment. However, the adoption of ongoing risk stratification (ORS), which dynamically reassesses risk by integrating longitudinal clinical data and treatment response, enables more precise long-term prognostic assessment and facilitates highly individualized management. Building upon recent guidelines, the 2026 KTA guideline has been further refined by incorporating robust evidence from large-scale national cohorts and comprehensive systematic reviews. These updated recommendations outline contemporary concepts of ORS, risk-adapted TSH suppression targets, optimized surveillance modalities for recurrence detection, and disease-specific long-term follow-up strategies. Reflecting the paradigm shift toward de-escalated treatment, this revision integrates evolved perspectives on TSH suppression intensity, the clinical interpretation of thyroglobulin levels, and tailored follow-up intervals. These evidence-based recommendations aim to minimize unnecessary treatment and excessive surveillance in the large proportion of patients with excellent prognosis after initial therapy, while ensuring that each patient receives appropriately tailored and effective long-term management.

Advancements in diagnostic technology have led to the improved detection of pancreatic neuroendocrine tumors (PNETs) and thus to an increase in the number of reported cases. Endoscopic ultrasound (EUS) technology, including in combination with contrast-enhanced harmonic imaging, aids in distinguishing PNETs from other tumors, while EUS-guided fine-needle aspiration or biopsy has improved the histological diagnosis and grading of tumors. The recent introduction of EUS-guided ablation using ethanol injection or radiofrequency ablation has offered an alternative to surgery in the management of PNETs. Comparisons with surgery have shown similar outcomes but fewer adverse effects. Although standardized protocols and prospective studies with long-term follow-up are still needed, EUS-based methods are promising approaches that can contribute to a better quality of life for PNET patients.

Background: This study aimed to evaluate the applicability of deep learning technology to thyroid ultrasound images for classification of thyroid nodules. Methods: This retrospective analysis included ultrasound images of patients with thyroid nodules investigated by fine-needle aspiration at the thyroid clinic of a single center from April 2010 to September 2012. Thyroid nodules with cytopathologic results of Bethesda category V (suspicious for malignancy) or VI (malignant) were defined as thyroid cancer. Multiple deep learning algorithms based on convolutional neural networks (CNNs) —ResNet, DenseNet, and EfficientNet—were utilized, and Siamese neural networks facilitated multi-view analysis of paired transverse and longitudinal ultrasound images. Results: Among 1,048 analyzed thyroid nodules from 943 patients, 306 (29%) were identified as thyroid cancer. In a subgroup analysis of transverse and longitudinal images, longitudinal images showed superior prediction ability. Multi-view modeling, based on paired transverse and longitudinal images, significantly improved the model performance; with an accuracy of 0.82 (95% confidence intervals [CI], 0.80 to 0.86) with ResNet50, 0.83 (95% CI, 0.83 to 0.88) with DenseNet201, and 0.81 (95% CI, 0.79 to 0.84) with EfficientNetv2_ s. Training with high-resolution images obtained using the latest equipment tended to improve model performance in association with increased sensitivity. Conclusion CNN algorithms applied to ultrasound images demonstrated substantial accuracy in thyroid nodule classification, indicating their potential as valuable tools for diagnosing thyroid cancer. However, in real-world clinical settings, it is important to aware that model performance may vary depending on the quality of images acquired by different physicians and imaging devices.

Alzheimer disease (AD) diagnosis is confirmed using a medley of modalities, such as the detection of amyloid-β (Aβ) neuritic plaques and neurofibrillary tangles with positron electron tomography (PET) or the appraisal of irregularities in cognitive function with examinations. Although these methods have been efficient in confirming AD pathology, the rising demand for earlier intervention during pathogenesis has led researchers to explore the diagnostic potential of fluid biomarkers in cerebrospinal fluid (CSF) and plasma. Since CSF sample collection is invasive and limited in quantity, biomarker detection in plasma has become more attractive and modern advancements in technology has permitted more efficient and accurate analysis of plasma biomolecules. In this study, we found that a composite of standard factors, Aβ40 and total tau levels in plasma, divided by the variation factor, plasma Aβ42 level, provide better correlation with amyloid neuroimaging and neuropsychological test results than a level comparison between total tau and Aβ42 in plasma. We collected EDTA-treated blood plasma samples of 53 subjects, of randomly selected 27 AD patients and 26 normal cognition (NC) individuals, who received amyloid-PET scans for plaque quantification, and measured plasma levels of Aβ40, Aβ42, and total tau with digital enzyme-linked immunosorbent assay (ELISA) in a blinded manner. There was difficulty distinguishing AD patients from controls when analyzing biomarkers independently. However, significant differentiation was observed between the two groups when comparing individual ratios of total-tau×Aβ40/Aβ42. Our results indicate that collectively comparing fluctuations of these fluid biomarkers could aid in monitoring AD pathogenesis.

Purpose: This multicenter, open-label, phase II trial evaluated the efficacy and safety of bortezomib combined with dexamethasone for the treatment of relapsed/refractory cutaneous T-cell lymphoma (CTCL) in previously treated patients across 14 institutions in South Korea. Materials and Methods: Between September 2017 and July 2020, 29 patients with histologically confirmed CTCL received treatment, consisting of eight 4-week cycles of induction therapy followed by maintenance therapy, contingent upon response, for up to one year. The primary endpoint was the proportion of patients achieving an objective global response. Results: Thirteen of the 29 patients (44.8%) achieved an objective global response, including two complete responses. The median progression-free survival (PFS) was 5.8 months, with responders showing a median PFS of 14.0 months. Treatment-emergent adverse events were generally mild, with a low incidence of peripheral neuropathy and hematologic toxicities. Despite the trend toward shorter PFS in patients with higher mutation burdens, genomic profiling before and after treatment showed no significant emergence of new mutations indicative of disease progression. Conclusion This study supports the use of bortezomib and dexamethasone as a viable and safe treatment option for previously treated CTCL, demonstrating substantial efficacy and manageability in adverse effects. Further research with a larger cohort is suggested to validate these findings and explore the prognostic value of mutation profiles.

Background: This study aimed to evaluate the applicability of deep learning technology to thyroid ultrasound images for classification of thyroid nodules. Methods: This retrospective analysis included ultrasound images of patients with thyroid nodules investigated by fine-needle aspiration at the thyroid clinic of a single center from April 2010 to September 2012. Thyroid nodules with cytopathologic results of Bethesda category V (suspicious for malignancy) or VI (malignant) were defined as thyroid cancer. Multiple deep learning algorithms based on convolutional neural networks (CNNs) —ResNet, DenseNet, and EfficientNet—were utilized, and Siamese neural networks facilitated multi-view analysis of paired transverse and longitudinal ultrasound images. Results: Among 1,048 analyzed thyroid nodules from 943 patients, 306 (29%) were identified as thyroid cancer. In a subgroup analysis of transverse and longitudinal images, longitudinal images showed superior prediction ability. Multi-view modeling, based on paired transverse and longitudinal images, significantly improved the model performance; with an accuracy of 0.82 (95% confidence intervals [CI], 0.80 to 0.86) with ResNet50, 0.83 (95% CI, 0.83 to 0.88) with DenseNet201, and 0.81 (95% CI, 0.79 to 0.84) with EfficientNetv2_ s. Training with high-resolution images obtained using the latest equipment tended to improve model performance in association with increased sensitivity. Conclusion CNN algorithms applied to ultrasound images demonstrated substantial accuracy in thyroid nodule classification, indicating their potential as valuable tools for diagnosing thyroid cancer. However, in real-world clinical settings, it is important to aware that model performance may vary depending on the quality of images acquired by different physicians and imaging devices.