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: and Purpose To compare the epidemiological and clinical features of the rare patients with cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) with age- and sex-matched controls in a nationwide cohort from South Korea. Methods: This observational cohort study analyzed newly diagnosed CADASIL patients aged at least 20 years and matched controls using data from the National Health Information Database for 2004–2022. The cumulative incidence of CADASIL was assessed by age and sex, and compared between regions. Neurologic and systemic diseases were compared between the CADASIL and control groups. Results: The study analyzed 816 CADASIL patients and 816 age- and sex-matched controls aged 56.8±15.2 years (mean±standard deviation), among whom 48.3% were male. The cumulative incidence of CADASIL was 1.86 per 100,000 people (95% confidence interval [CI]=1.85– 1.87 per 100,000), and peaked at 60–69 years of age. In terms of regional distribution, the incidence was highest for Jeju, at 39.67 per 100,000 (95% CI 37.84–41.49 per 100,000). Neurologic diseases were more frequent in CADASIL patients, including Alzheimer’s disease (33.1% vs.20.0%), vascular dementia (84.9% vs. 5.0%), epilepsy (34.6% vs. 15.9%), stroke (70.7% vs. 27.6%), parkinsonism (18.9% vs. 11.0%), and depression (60.8% vs. 44.9%). Systemic diseases such as diabetes mellitus (78.9% vs. 68.9%) were also more common in CADASIL patients, while cancer (27.9% vs. 38.7%) and myocardial infarction (10.0% vs. 13.6%) were less common than in controls. The onset ages of all diseases were lower in CADASIL patients. Conclusions This study has provided a precise nationwide estimate of the CADASIL incidence and its regional distribution in South Korea. CADASIL patients showed higher incidence rates and earlier onsets of diverse clinical manifestations.

Background/Aims: Left ventricular ejection fraction (LVEF) is a key echocardiographic parameter for assessing LV systolic function, guiding the management of many cardiovascular diseases, including heart failure (HF). While traditional electrocardiography (ECG) has been widely used in clinical practice, it has limitations in predicting LVEF. This study investigated the impact of integrating ECG data with metadata, such as age, N-terminal pro B-type natriuretic peptide (NT-proBNP), and sodium levels, to enhance the accuracy of LVEF prediction, especially in HF with reduced ejection fraction (HFrEF, LVEF ≤ 40%). Methods: This retrospective study analyzed ECG and metadata from two tertiary teaching hospitals in Korea. A deep neural network (EfficientNet B3) was trained to predict LVEF, incorporating clinical metadata alongside ECG inputs. Model performance was assessed using the area under the curve (AUC) and the coefficient of determination (R2). Results: The artificial intelligence (AI) model achieved an AUC of 0.95 when ECG data were combined with age, NT-proBNP, and sodium levels, outperforming models relying on ECG alone (AUC = 0.90). The integration of metadata significantly improved the prediction accuracy, particularly for HFrEF cases. The specificity of the model remained high (96.9%), but sensitivity was relatively low (54.8%), indicating its potential as a screening tool for HFrEF. Conclusions The combination of ECG and metadata results using AI enhances the predictive accuracy of HFrEF detection. This approach offers a scalable and noninvasive method for HF screening and risk stratification, particularly in resource-limited settings. Further validation in diverse populations is needed to confirm its clinical utility.

Purpose: Autism spectrum disorder (ASD) exhibits heterogeneous developmental trajectories; however, longitudinal studies using the Korean Childhood Autism Rating Scale (K-CARS) are scarce. This study examined diagnostic changes and related developmental characteristics through repeated K-CARS assessments. Methods: We retrospectively reviewed the medical records of children who underwent repeated K-CARS assessments between May 2021 and December 2024 at Gyeongsang National University Hospital. Based on diagnostic status at the initial (T1) and follow-up (T2) evaluations, participants were classified as having persistent ASD (ASD at T1 and T2), emerging ASD (non-ASD at T1 but ASD at T2), or desisting ASD (ASD at T1 but non-ASD at T2). Developmental profiles were evaluated using the social quotient (SQ), visual-motor integration (VMI), and language quotients. Results: Forty-three children (32 boys; median age, 2.9 years at T1 and 4.3 years at T2) were included. Twenty-two met ASD criteria at T1, and 15 (68%) retained the diagnosis at T2. Across the cohort, 15 (35%) had persistent ASD, 21 (49%) had emerging ASD, and seven (16%) had desisting ASD. The desisting group showed higher baseline VMI and better outcomes at follow-up. The emerging group initially had higher SQ and VMI than the persistent group, but these differences disappeared over time. Higher baseline VMI was associated with desisting status and higher baseline SQ with emerging ASD (odds ratios, 3.14 and 2.59 per standard deviation increase, respectively; P=0.06 and P=0.07). Conclusion Early ASD diagnoses were generally stable yet variable, supporting repeated assessment. Baseline VMI and SQ may relate to later diagnostic changes.

Background: s/Aims: Phase angle (PhA), as measured by bioelectrical impedance analysis, provides insights into hydration and nutritional status, making it a prognostic indicator of frailty. While low preoperative PhA has been linked to postoperative complications in cancer patients, its predictive value in individuals undergoing pancreaticoduodenectomy (PD) has not been thoroughly investigated.This study aims to evaluate the clinical utility of preoperative PhA in predicting postoperative complications for patients undergoing PD. Methods: Among 41 patients who underwent PD at Seoul National University Hospital between September and December 2024, 35 were included in the analysis after excluding 6 patients who had concomitant blood vessel or other organ resections. Patients were divided into low (Comprehensive Complication Index [CCI] ≤ 20) and high (CCI > 20) complication groups based on the CCI, derived from the Clavien–Dindo classification. The differences in PhA between the two groups were analyzed, and logistic regression was performed to assess the relationship between PhA and CCI. Results: The mean PhA was significantly lower in the high-CCI group compared to the low-CCI group (5.7° vs. 6.7°, p = 0.025). Multivariate logistic regression analysis indicated that PhA (odds ratio: 0.17; 95% confidence interval: 0.04–0.68; p = 0.012) was an independent predictor of high CCI. A low preoperative PhA was associated with an increased risk of postoperative complications following PD. Conclusions Preoperative PhA may serve as a valuable predictive indicator of postoperative complications after PD, enabling the identification of patients who could benefit from preoperative prehabilitation, including nutritional support.

Background: The 2020 European Society of Cardiology (ESC) 0-hr/1-hr algorithm using high-sensitivity cardiac troponin I (hs-cTnI) for non-ST-segment elevation acute coronary syndrome (NSTE-ACS) aims at early diagnosis and shorter emergency department (ED) stays. While this algorithm has been well-established in controlled studies, real-world implementation remains challenging. We evaluated the algorithm’s clinical performance and risk stratification capability in patients with chest pain or discomfort. Methods: We measured hs-cTnI in 4,678 patients suspected of NSTE-ACS between August 2022 and July 2023, using an Atellica IM Analyzer (Siemens Healthineers, Erlangen, Germany). We categorized patients into rule-in, observe, or rule-out groups according to the algorithm and assessed its diagnostic performance for NSTE-ACS. The final diagnosis of NSTE-ACS was adjudicated by two independent physicians. Additionally, we evaluated 30-day all-cause mortality, hazard risk, and ED length of stay across the three groups. Results: The algorithm categorized 3,408 (72.9%), 573 (12.2%), and 697 (14.9%) patients into the rule-out, observe, and rule-in groups, respectively. Among 90 patients diagnosed as having NSTE-ACS, none were falsely categorized into the rule-out group. Survival analysis revealed significant differences (P < 0.001), with Cox hazard ratios of 2.38 (95% confidence interval: 1.20–4.71) and 6.39 (3.45–11.86) in the observe and rule-in groups, respectively. ED stays shortened in the order of rule-out, observe, and rule-in groups (P < 0.001). Conclusions The 2020 ESC 0-hr/1-hr algorithm demonstrates excellent diagnostic accuracy without false rule-outs and effective risk stratification, and contributes to efficient ED throughput, supporting its clinical utility in real-world emergency settings.

Background: Transthyretin amyloidosis, a protein-misfolding disorder characterized by systemic amyloid deposition, can be classified as wild-type transthyretin amyloidosis (ATTRwt) or hereditary transthyretin amyloidosis (ATTRv), depending on the presence of transthyretin (TTR) gene variants. We examined the genetic distribution of TTR variants in Korean patients diagnosed with ATTRv. Methods: We retrospectively reviewed 801 participants who underwent TTR analysis at Samsung Medical Center from 2012 to 2024. The participants were categorized into two groups: in-house probands or relatives, and externally referred probands or relatives. Results: Pathogenic or likely pathogenic TTR variants were detected in 36 of 165 in-house probands (21.8%), among which D38A was the most frequent variant (50.0%; 18/36), followed by M13dup and E89K (8.3% each). Among referred probands, D38A was predominant (54.5%; 12/22), followed by M13dup (22.7%; 5/22). Cardiac amyloid involvement was the most common manifestation, observed in 97.2% (35/36) of in-house probands with ATTRv, followed by peripheral nervous system (PNS; 94.4%) and autonomic nervous system (ANS; 88.9%) involvement. In contrast, ANS involvement was most prevalent among in-house relatives who underwent organ evaluation (61.5%; 24/39), followed by cardiac (52.1%; 25/48) and PNS (48.7%; 19/39) involvement. Five of the eight in-house relatives harboring M13dup (62.5%) showed organ involvement, primarily in the ANS, supporting the pathogenicity of this variant. Conclusions This study provides the largest single-institution dataset of Korean patients with ATTRv, incorporating systematic organ assessments. The predominance of the unique TTR variants D38A and M13dup delineates a distinct genetic landscape that may facilitate accurate and timely diagnosis of ATTRv in the Korean population.