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.

Background/Aims: Patients with atrial fibrillation (AF) and end-stage kidney disease (ESKD) require careful anticoagulation because thrombotic and bleeding risks are both elevated. We evaluated the efficacy and safety of warfarin, direct oral anticoagulants (DOACs), and no anticoagulation in Korean patients with ESKD and AF. Methods: In this multicenter retrospective study, we included 933 patients with ESKD and nonvalvular AF treated between 2010 and 2023. Patients were assigned to three groups by initial treatment: no anticoagulation (n = 604), warfarin (n = 197), or DOACs (n = 132). The primary efficacy outcome was ischemic stroke or systemic embolism (IS/SE); the primary safety outcome was major bleeding (MB). Secondary outcomes were intracranial hemorrhage (ICH), gastrointestinal bleeding (GIB), and all-cause mortality. Inverse probability of treatment weighting was used to adjust for confounding. Results: Both warfarin (adjusted hazard ratio [aHR], 0.55) and DOACs (aHR, 0.36) significantly reduced the risk of IS/SE compared with no anticoagulation. However, warfarin increased MB risk compared with no anticoagulation (aHR, 2.69), including ICH and GIB. DOACs also increased MB risk versus no anticoagulation (aHR, 1.37), driven primarily by ICH. Compared with warfarin, DOACs showed a lower MB risk (aHR, 0.51). Both warfarin and DOACs reduced all-cause mortality relative to no anticoagulation (aHR, 0.53 and 0.57, respectively). Conclusions Among Korean patients with ESKD and AF, both warfarin and DOACs reduced IS/SE but increased MB. Given their lower MB risk than warfarin, DOACs may be preferable for anticoagulation in this high-risk population.

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: The accurate laboratory-based detection of respiratory viruses, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is essential for effective patient management and infection control in the post–coronavirus disease 2019 era. In this study, the performance of the PowerChek Respiratory Virus Panels 1–4 assay (Kogene Biotech) in detecting non-SARS-CoV-2 respiratory viruses and SARS-CoV-2 was compared with those of two established commercial assays. Methods: Residual clinical respiratory specimens collected between December 2023 and February 2024 were retested using the PowerChek assay. Of the 129 specimens retested, 80 had tested positive for 14 non-SARS-CoV-2 respiratory virus targets in the Allplex Respiratory Panels 1–3 assay (Seegene) and 49 had been tested using the Alinity m SARS-CoV-2 assay (Abbott; 20 positive and 29 negative for SARS-CoV-2). Agreement, Cohen’s kappa, and discordant results were assessed. Results: For the 14 non-SARS-CoV-2 respiratory virus targets, the virus-specific overall percent agreement (OPA) ranged from 95.0% to 100%, the positive percent agreement (PPA) ranged from 66.7% to 100%, and the negative percent agreement (NPA) ranged from 96.0% to 100%, with kappa values of 0.64–1.00. Lower agreements were observed for human coronavirus OC43 and influenza A virus. For SARS-CoV-2 detection, the OPA was 98.0% (PPA, 95.0%; NPA, 100%; kappa, 0.96). Conclusion The detection performance of the PowerChek assay was comparable to those of the established assays for most respiratory virus targets, with lower agreement observed for some targets. These features support its practical utility for the routine multiplex molecular detection of respiratory viruses, including SARS-CoV-2.

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: Alpha-fetoprotein (AFP) and its isoform AFP-L3 are well-established serum biomarkers for hepatocellular carcinoma (HCC), a common malignancy and a leading cause of cancer-related mortality worldwide. Current methods for measuring these biomarkers are primarily lectin-based assays including the liquid-phase binding assay (LiBA) and liquid chromatography–tandem mass spectrometry (LC-MS/MS), both of which have limitations in diagnostic sensitivity and clinical utility for samples with low AFP concentrations. We aimed to develop a lectin-independent LC-MS/MS method for quantifying fucosylated AFP proteins (AFP-Fuc%). Methods: We conducted analytical validation, including method comparisons, over 2 months. The analytical sensitivity and diagnostic performance of this method were evaluated using 525 human serum samples—235 from HCC patients and 290 from non-HCC individuals—and compared with those of LiBA, which measured AFP-L3 levels. Results: The LC-MS/MS method demonstrated acceptable within-laboratory imprecision (CVs < 17.1%) without detectable bias, carryover, or matrix effects. Our method exhibited a broader linear dynamic range (spanning five orders of magnitude) and 10-fold higher analytical sensitivity than LiBA. The diagnostic performance of our method was significantly superior to that of LiBA, particularly in patients with low AFP concentrations ( < 7 ng/mL, P < 0.001), with improved accuracy, sensitivity, and precision at a specificity of 96.2%. Conclusions The validated LC-MS/MS method demonstrated robust analytical performance and superior diagnostic accuracy over LiBA for HCC diagnosis while avoiding the inherent limitations of lectin-based assays. Our LC-MS/MS assay shows promise for early HCC detection and may contribute to enhanced patient care.

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.