Objectives: This study examined the factors associated with stages of change (SOC) in reducing sugar intake among adults, applying the theory of planned behavior. Methods: An online survey was conducted among adults aged 19–49 years residing in Seoul, Korea. Based on their SOC in reducing sugar intake, participants (n = 380) were categorized into a pre-action group (45.3%) and an action group (54.7%). Statistical analysis was performed using χ2-test, analysis of covariance, and one-way analysis of variance with linear contrast. Results: The consumption frequency of sugary foods was significantly higher in the pre-action group than in the action group (P < 0.001). Compared with the action group, participants in the pre-action group perceived the advantages of sugar intake more favorably (P < 0.001), perceived the disadvantages less strongly (P = 0.002), and reported greater influence from significant others (P = 0.004). In contrast, participants in the action group agreed less with insufficient knowledge/skills (P < 0.001), had greater control over the facilitating factors of sugar intake (P < 0.001), and had stronger control beliefs in situations promoting sugar intake (P < 0.001). Behavioral beliefs (P < 0.001) and control beliefs (P < 0.001) showed a significant linear trend across the five SOC, whereas subjective norms did not (P = 0.275). Conclusion Psychosocial factors related to sugar intake reduction clearly differed between the SOC groups. In the pre-action group, nutrition education should emphasize lowering the perceived benefits of sugar intake while increasing awareness of its adverse consequences. Strengthening the perception of control over sugar intake is important, despite the factors or situations promoting sugar intake. This can be achieved by providing practical tips and developing skills to reduce sugar intake. For the action group, it is necessary to maintain the reduced sugar intake through continual support and encouragement.

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.

Secondary rhabdoid tumors (RTs) with atypical teratoid/rhabdoid tumor-like features rarely arise from, or coexist with, pleomorphic xanthoastrocytomas (PXAs), and their clinicopathological and molecular characteristics remain poorly understood. We report a 17-year-old girl with a temporal lobe mass that, upon gross total resection, pathologically contained both RT and PXA components. Immunohistochemistry revealed loss of INI1 expression restricted to the RT component, while the PXA area retained INI1. Next-generation sequencing identified a shared BRAF::TRIM24 fusion and homozygous deletion of CDKN2A/2B in both components, indicating a shared clonal origin. Additionally, a germline ATM frameshift mutation (c.5288_5289insGA) was identified in both tumor components, making the first such report in central nervous system tumors. SMARCB1 loss was confined to the RT component, further supporting the hypotheses of clonal evolution and secondary transformation. Despite gross total resection, craniospinal irradiation, and chemotherapy, the patient developed rapid leptomeningeal dissemination and died 5 months after surgery. This case provides clinicopathological and molecular evidence for clonal evolution and secondary transformation of PXA into an RT. The presence of germline ATM mutation may have therapeutic and biological relevance. Further studies are required to clarify the pathogenesis and optimal management of these rare and aggressive tumors.

Background: and Purpose: To assess the long-term effectiveness, safety, and economic viability of recently approved Alzheimer’s disease (AD) therapies, as well as to evaluate the real-world application of novel diagnostics among AD patients with diverse comorbidities, comprehensive real-world data (RWD) analysis is essential. The Korean JOint RegistrY for ALZheimer’s Treatment and Diagnostics (JOY-ALZ) endeavors to create a registry of RWD derived from clinical practice on new diagnostic methods and therapeutic agents for AD introduced in Korea since 2021. Methods: Participants must fulfill all the following: 1) be at least 19 years old; 2) be actively receiving, scheduled to initiate, or undergoing evaluation for any AD disease-modifying treatment; 3) have completed amyloid positron emission tomography or cerebrospinal fluid AD immunoassay (a positive result is not essential for participation); 4) have a clinical classification of cognitively unimpaired, mild cognitive impairment, or probable AD dementia. Data generated during routine care is segmented into a minimum dataset, extended dataset, and research-only dataset requiring extra consent. Assessments encompass clinical, cognitive, functional, neurobehavioral, neuroimaging, and biomarker evaluations, in addition to systematic monitoring of new AD treatments and their safety.Data are collected and monitored at baseline, at semiannual intervals during the initial 2 years, and then annually up to 2034. To date, 46 medical centers will participate in JOY-ALZ. Conclusions JOY-ALZ is expected to promote understanding of the long-term clinical outcomes, safety, and cost-effectiveness of recently introduced diagnostics and treatments for AD, thereby supporting the progress of precision medicine in AD care and diagnosis.

Background/Aims: Cardiovascular disease remains a major cause of mortality in patients with metabolic dysfunction-associated steatotic liver disease (MASLD). This study evaluated the association between subclinical carotid atherosclerosis (SCA) and MASLD or MASLD and increased alcohol intake (MetALD) in asymptomatic individuals. Methods: This cross-sectional study included 56,889 adults undergoing health check-ups in South Korea. Hepatic steatosis was diagnosed by ultrasound, and SCA was defined by carotid plaques or increased intima-media thickness. Liver fibrosis was evaluated using the fibrosis-4 index and elastography. Results: SCA was identified in 13.5%. MASLD and MetALD were significantly associated with SCA in models adjusted for demographic and lifestyle factors (adjusted odds ratio [aOR], 1.26;95% confidence interval [CI], 1.19 to 1.33; aOR, 1.43; 95% CI, 1.30 to 1.58; respectively, p<0.001for both). However, these associations attenuated and lost statistical significance when metabolic risk factors were further adjusted. The risk of SCA increased with greater hepatic steatosis and liver fibrosis severity. In patients with MASLD, aORs were 1.70 (hepatic steatosis index >36),1.23 (fibrosis-4 index ≥1.3), and 1.78 (liver stiffness measurement ≥5.6 kPa), compared to indi-viduals without MASLD. Similar trends were observed in the MetALD group. Additionally, hyper-tension and clustering of ≥3 cardiometabolic risk factors were significantly associated with SCA inthe MASLD group, supporting the role of metabolic burden in SCA development. Conclusions MASLD and MetALD were associated with increased SCA risk, particularly in individuals with hepatic steatosis and fibrosis. These findings suggest that metabolic burden and liver disease severity jointly contribute to subclinical atherosclerosis risk.

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.

Objectives: Large language models (LLMs) demonstrate remarkable potential in healthcare communication. However, whether they can process complex, high-volume medical information, such as stroke-related content, remains insufficiently validated. This study aimed to evaluate the natural language processing capabilities of LLMs in handling such content and to develop an evaluation instrument. Methods: A survey compared educational materials generated by two LLMs (ChatGPT 4.0 and Claude 3) with neurologist-authored content on stroke. The materials were based on two clinical scenarios representing distinct stroke etiologies: cardioembolism and large-artery atherosclerosis. They were evaluated in terms of accuracy, legality, ethics, comprehensiveness, and information delivery. Scores for comprehensiveness and information delivery were compared according to participants’ agreement with the use of LLMs in healthcare. Results: ChatGPT received the highest scores across all domains, except for legality in Scenario 2. In Scenario 1, the ranking for accuracy and summarization of clinical information was, from highest to lowest, ChatGPT, Claude, and the neurologist (η2 = 0.140, p < 0.001; η2 = 0.175, p < 0.001). The same hierarchy was observed in Scenario 2 for accuracy (η2 = 0.077, p < 0.001) and summarization (η2 = 0.194, p < 0.001). Participants who agreed with the use of LLMs in healthcare assigned higher scores for the comprehensiveness (Scenario 1, p = 0.005; Scenario 2, p = 0.007) and information delivery (Scenario 1, p = 0.003; Scenario 2, p = 0.026) of ChatGPT-generated materials than participants who did not agree. Conclusions LLMs demonstrated adequate capability to convey complex content, such as stroke-related information, in an accessible and understandable manner for non-experts.

Objectives: This study evaluated the feasibility of voice recognition-based electronic medical record (EMR) documentation for periodontal probing in dentistry, particularly emphasizing Korean-English bilingual speech patterns and real-world clinical conditions. Methods: Experiments were conducted in a dental chair setting during routine clinical hours. Environmental noise levels were measured, and two microphone types (stationary and pin-type) were evaluated. Periodontal probing phrases composed of three-digit numbers and positional terms were used for speech recognition. Consistent with common clinical practice in Korea, numerical values were spoken in Korean, whereas positional terms were spoken in English. Two speech-to-text application programming interfaces, Google Cloud Speech-to-Text and Naver Clova Speech Recognition, were assessed. Recognition accuracy was evaluated for both numerical components and complete bilingual phrases. Results: The mean environmental noise level was 60.65 dB and was minimally influenced by activity at adjacent dental chairs. The stationary microphone failed to capture speech effectively, whereas the pin-type microphone demonstrated stable recognition performance. For three-digit number recognition, accuracy was 88.3% with Google and 96.8% with Naver. For full-phrase recognition, complete matching was achieved in 36.7% of cases for Google and 52.5% for Naver. Partial recognition occurred more frequently for numerical components than for English positional terms. Conclusions Voice recognition-based EMR documentation for periodontal probing demonstrated preliminary feasibility in a dental clinical environment; however, performance was influenced by Korean-English bilingual speech patterns. These findings suggest that bilingual speech characteristics should be considered when implementing voice recognition systems in dental EMR workflows. Further optimization is required before routine clinical application.

Purpose: To develop and validate an artificial intelligence (AI)-based personalized outcome prediction model for upper-urinary tract urothelial carcinoma patients undergoing radical nephroureterectomy. Materials and Methods: Data from patients who underwent radical nephroureterectomy between 2010 and 2020 across three hospitals were retrospectively analyzed. A model was developed using one tertiary center’s data and externally validated with data from two other hospitals. An AI model using XGBoost as risk estimator and bootstrapped Weibull Accelerated Failure Time model for 10-year survival probability was employed. Hyperparameter tuning used Optuna method. Model efficacy was assessed using concordance index, average Brier score, D-calibration, and six-month interval time-dependent area under the curve (AUC). Results: Of 1,039 patients, 627 qualified after excluding 50 with neoadjuvant chemotherapy. Model development used 564 patients (507 training, 57 test) with 9:1 stratified random split, plus 63 for internal validation and 362 for external validation. Significant parameters included preoperative glomerular filtration rate (p<0.001), hydroureteronephrosis (p=0.013), pathological N stage (p<0.001), concurrent carcinoma in situ (p<0.001), disease progression (p<0.001), and survival rate (p<0.001). Disease-free survival (DFS) model’s concordance index: internal validation 0.789, external validations 0.734 and 0.771. Overall survival (OS) model’s concordance index: internal validation 0.819, external validations 0.780 and 0.771. Mean time-dependent AUC was 0.66–0.77 for DFS and 0.67–0.80 for OS during 10-year periods. Conclusions AI-based model effectively predicts disease-free and OS outcomes for upper-urinary tract urothelial carcinoma patients with post-radical nephroureterectomy, showcasing robust performance across multicenter settings.