Boramae Medical Center

This study proposes a wrist radiography-based deep learning model for identifying radiographic features of metabolic bone disease (MBD) of prematurity and evaluate the impact of its decision support. This retrospective study included preterm infants with birth weights under 1500g, born at Seoul National University Hospital (internal dataset: 814 subjects) and Seoul National University Bundang Hospital (external dataset: 261 subjects). Demographic and clinical information and wrist radiographs (postnatal ages: 4-8 weeks) were collected. An internal dataset was used to develop and train identification models and an external dataset was used for validation. Performance was evaluated using the area under the receiver operating characteristic curve (AUROC) and performance quality was compared based on paired t- and Wilcoxon signed-rank tests. The DenseNet-based model exhibited the highest performance quality with AUROC of 0.961 (sensitivity: 94.4%, specificity: 91.2%, accuracy: 92.0%). The external validation study yielded an AUROC of 0.927, indicating its potential applicability in a broad clinical setting. The reader study using external data demonstrated an improved reading performance, especially for non-radiologists (65.4% to 78.7% accuracy; P = 0.008, among pediatricians). The developed model can assist clinicians, especially non-radiologists, in identifying radiographic signs suggestive of MBD, enabling timely diagnosis and treatment to prevent disease progression.

Survival outcomes for infants born at 22–23 weeks’ gestation vary widely across neonatal units. This national, prospective cohort study evaluated 919 infants born at 22–23 weeks’ gestation in South Korea between 2013 and 2022, using Korean Neonatal Network data. Infants were categorized based on the level of neonatal care: 785 in lower-level centers (Group A) and 134 in higher-level centers (Group B). Survival was significantly higher in Group B (64.9%) compared to Group A (29.3%) (P < 0.0001). Early deaths occurred more frequently and earlier in Group A. Proactive care—including antenatal corticosteroids, antenatal antibiotics, and immediate surfactant administration—was more common in Group B. Antenatal corticosteroid was significantly associated with reduced risk of death (hazard ratio 0.58; 95% confidence interval, 0.49–0.69; P < 0.0001). The timing of rapid decline in survival was delayed in higher-level centers. In addition, classifying institutions into higher- and lower-level groups according to the survival of infants born at 22–23 weeks’ gestation (≥50% vs. <50%) provides a good reflection of the quality of neonatal care. These findings highlight the importance of proactive care and timely in utero transfer to higher-level units in improving survival for peri-viable infants.Supplementary InformationThe online version contains supplementary material available at 10.1038/s41598-025-28428-1.

BackgroundThe COVID-19 pandemic has highlighted the importance of understanding the complex interactions between pre-existing conditions, such as ischaemic heart disease (IHD), and mortality risk. This study aims to investigate the associations among COVID-19 mortality, the presence of IHD, and the use of angiotensin receptor blockers (ARBs) and angiotensin-converting-enzyme inhibitors (ACEIs) by leveraging the South Korean National Health Insurance Service (NHIS) big data.MethodsWe conducted a retrospective cohort study of 30,056 patients with COVID-19 from the NHIS. The study population was stratified into four groups based on IHD status and the use of ACEI/ARBs. To assess their effects on mortality, we applied inverse probability of treatment weighting (IPTW) to balance baseline covariates, followed by a weighted logistic regression. The interaction between IHD and ACEI/ARB use was evaluated on both multiplicative (interaction term) and additive scales (Relative Excess Risk Due to Interaction, RERI), supplemented by an age-stratified analysis (≤ 70 vs. >70 years).ResultsAmong 30,056 COVID-19 patients, we identified a significant interaction between IHD and ACEI/ARB use on mortality after adjusting for confounders. The main finding revealed that among patients with IHD, ACEI/ARB treatment was associated with 74% lower odds of mortality compared to non-treatment (Adjusted OR: 0.26, 95% CI: 0.08–0.92, p = 0.037). This protective interaction was strongly age-dependent, remaining statistically significant only in patients older than 70 (Interaction OR: 0.53, 95% CI: 0.27–0.99; p = 0.048). Furthermore, a significant antagonistic interaction on the additive scale (RERI: − 1.77, 95% CI − 3.04 to − 0.51; p = 0.006) confirmed a combined protective effect greater than the sum of the individual effects.ConclusionsThis study leverages the NHIS big data to provide a comprehensive analysis of the complex interactions among IHD, ACEI/ARB use, demographic factors, and comorbidities in the context of COVID-19 mortality. Our findings suggest a 45% reduction in the odds of mortality for IHD patients taking ACEI/ARB, particularly those over 70 years, but randomised controlled trials are needed before clinical guideline changes. The findings highlight the protective effect of ACEI/ARB in patients with IHD and emphasize the importance of personalized treatment approaches considering patient characteristics, pre-existing conditions, and medication use.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12879-025-11885-4.

Impaired early graft function effects differ by donor type: living donors show increased rejection/graft failure and deceased donors show mortality risk. Despite high-risk incompatible transplants, living donor recipients have low impaired graft function rates (4.5% versus 24.7% in deceased donors). Slow graft function is a distinct phenotype requiring recognition beyond traditional delayed graft function classification, with donor-specific implications. With the rise of high-risk living donor kidney transplantation, the effect of early graft function (EGF) on transplant outcomes remains unclear. In this retrospective multicenter study, we classified kidney transplantation recipients (KTRs) based on EGF and donor type. EGF within the first post-transplant week was classified as immediate graft function, slow graft function (SGF), or delayed graft function (DGF), with impaired EGF defined as SGF or DGF. The primary outcomes included biopsy-proven acute rejection (BPAR) within 1 year, death-censored graft failure (DCGF), and overall mortality. Among 3261 KTRs, 365 (11.2%) experienced impaired EGF, including 190 (5.8%) with SGF and 175 (5.4%) with DGF. In living donor KTRs, impaired EGF was significantly associated with an increased risk of 1-year BPAR (adjusted hazard ratio [aHR], 2.13; 95% confidence interval [CI], 1.33 to 3.39) and DCGF (aHR, 2.49; 95% CI, 1.29 to 4.82) but not mortality. Both SGF and DGF increased the risk of BPAR, while only DGF significantly elevated the risk of DCGF. In deceased donor KTRs, impaired EGF was associated with a higher risk of both DCGF (aHR, 2.18; 95% CI, 1.43 to 3.31) and mortality (aHR, 2.30; 95% CI, 1.52 to 3.49) with SGF and DGF demonstrating similar patterns. Notably, prolonged DGF (≥7 days) was linked to progressively worse outcomes. The effect of impaired EGF varies by donor type. In living donor KTRs, impaired EGF increased the risks of BPAR and DCGF, particularly in cases of DGF. In deceased donor KTRs, impaired EGF elevated the risks of DCGF and mortality but not BPAR, highlighting the need for tailored strategies to optimize EGF.

PurposeThis study aimed to investigate the relationship between truncal muscle mass, particularly the skeletal truncal muscle mass index (sTMI), and overactive bladder (OAB) symptoms in adult men, using bioelectrical impedance analysis (BIA).Materials and MethodsWe retrospectively analyzed health screening data from 5,475 men aged ≥40 years collected between 2014 and 2022. OAB was defined as an OAB Symptom Score (OABSS) ≥3 and urgency score ≥2, with moderate-to-severe OAB defined as OABSS ≥6 and urgency score ≥2. Body composition metrics, including fat-free mass (FFM), total muscle mass (TMM), and truncal muscle mass (whole and skeletal), were measured via BIA. The sTMI was calculated by dividing skeletal truncal muscle mass by body mass index (BMI). Logistic regression and receiver operating characteristic (ROC) analyses were conducted to assess predictors of OAB.ResultsThe overall OAB prevalence was 10.6%. In univariate analysis, FFM (odds ratio [OR] 0.983, p=0.013), TMM (OR 0.982, p=0.010), and sTMI (OR 0.447, p=0.025) were inversely associated with OAB symptoms. However, in multivariate analysis, only sTMI remained a significant independent predictor of moderate-to-severe OAB (OR 0.486, p=0.036). ROC analysis showed that sTMI had better predictive performance for severe OAB (area under the curve [AUC] 0.721) compared to age (AUC 0.706).ConclusionssTMI, a BIA-based index reflecting truncal skeletal muscle normalized to BMI, is an independent predictor of moderate-to-severe OAB in men. This suggests a potential role of muscle composition in OAB pathophysiology and risk stratification.

Abstract Background and Objectives Fontan circulation alters cardiovascular hemodynamics to maintain circulation using a single ventricle, which may consequently increase the risk of thromboembolism. This highlights the need for effective thromboprophylaxis strategies. This study assessed optimal thromboprophylaxis regimens for patients with Fontan circulation through a comprehensive meta-analysis of literature focused on personalized, ethnicity-based approaches. Methods PubMed, Embase, and Cochrane Library databases were searched to identify studies reporting the thromboembolic and bleeding outcomes of patients with Fontan circulation. Results Thirty reports—four randomized controlled trials and 26 cohort studies—were analyzed. Aspirin (risk ratio [RR], 0.46; 95% confidence interval [CI], 0.2–1.08; p = 0.07), warfarin (RR, 0.40; 95% CI, 0.24–0.65; p &lt; 0.001), and direct oral anticoagulants (DOACs) (RR, 0.22; 95% CI, 0.01–7.57; p = 0.4) all showed a trend toward reduced thromboembolic risk, compared with no antithrombotic therapy; however, only warfarin was statistically significant. In the East Asian subgroup, aspirin significantly decreased thromboembolic risk, compared with no intervention (RR, 0.31; 95% CI, 0.16–0.58; p &lt; 0.001), and was statistically more effective than warfarin (RR, 0.57; 95% CI, 0.37–0.88; p = 0.01). No significant differences in bleeding risk existed between the aspirin and warfarin groups or between any-thromboprophylaxis and no-thromboprophylaxis groups. Conclusions Compared with no intervention, thromboprophylaxis in patients with Fontan circulation reduces thromboembolic risk. Although our findings should be carefully interpreted because of the limited data, they indicate that aspirin may be more effective than warfarin in East Asian patients, underscoring the need for further research into ethnicity-tailored thromboprophylaxis strategies.

Limited data exist on managing psoriasis and psoriatic arthritis (PsA) in survivors of major adverse cardiovascular events (MACEs). To investigate the risk of recurrent and new-onset MACEs associated with systemic therapies for psoriasis and PsA. A retrospective cohort study using Korean health insurance data (January 2008-October 2021) included patients diagnosed with psoriasis or PsA treated with biologics, nonbiologic systemic therapy, or phototherapy. The primary outcome was MACE (acute myocardial infarction, stroke, cardiac arrest, unstable angina, or heart failure). Multivariable time-dependent Cox regression models were used for risk analysis. The study included 183,212 patients, yielding 259,475 treatment episodes. Biologic therapy was associated with a lower risk of new-onset and recurrent MACEs compared to phototherapy (adjusted hazard ratio, 0.454; 95% confidence interval [CI], 0.359-0.574; 0.343, 95% CI, 0.245-0.479, respectively). Nonbiologic systemic therapy showed a lower MACE risk than did phototherapy only in patients with a history of MACE (adjusted hazard ratio, 0.789; 95% CI, 0.658-0.946). Observational design limits causal inference and may involve residual confounding. The study supports the use of biologics in patients with moderate-to-severe psoriasis or PsA, particularly those with a MACE history where treatment options are limited.

ObjectiveWe previously developed and validated an artificial intelligence-based electrocardiogram (ECG) analysis tool (ECG Buddy) in a Korean population. This study investigated the performance of this tool in a US population, specifically assessing the left ventricular (LV) dysfunction score and LV ejection fraction (LVEF)-ECG feature for predicting LVEF <40%. The study used N-terminal pro-B-type natriuretic peptide (NT-ProBNP) as a comparator.MethodsWe identified emergency department (ED) visits from the MIMIC-IV dataset with information on LVEF <40% or ≥40% and matched 12-lead ECG data recorded within 72 hours of the ED visit. The performance of ECG Buddy’s LV dysfunction score and the LVEF-ECG feature was compared with those of NT-ProBNP using area under the receiver operating characteristic curve (AUC) analysis.ResultsA total of 22,599 ED visits were analyzed. The LV dysfunction score had an AUC of 0.905 (95% confidence interval [CI], 0.899–0.910), with a sensitivity of 85.4% and specificity of 80.8%. The LVEF-ECG feature had an AUC of 0.908 (95% CI, 0.902–0.913), sensitivity of 83.5%, and specificity of 83.0%. NT-ProBNP had an AUC of 0.740 (95% CI, 0.727–0.752), with a sensitivity of 74.8% and specificity of 62.0%. The ECG-based predictors demonstrated superior diagnostic performance compared to NT-ProBNP (all P<0.001). In the sinus rhythm subgroup, the LV dysfunction score achieved an AUC of 0.913 and LVEF-ECG had an AUC of 0.917, both outperforming NT-ProBNP (AUC, 0.748; 95% CI, 0.732–0.763; all P<0.001).ConclusionECG Buddy demonstrated superior accuracy compared with NT-ProBNP in predicting LV systolic dysfunction, validating its utility in a US ED population.

Abstract Background This study aimed to investigate the relationship between personality traits, academic burnout, and academic engagement among dental students with emotion regulation as a mediating role. It sought to identify personality predictors within the HEXACO model and compare how these traits directly and indirectly affect students’ academic engagement and burnout. Methods The participants were 228 dental students from School of Dentistry. Data were collected using the HEXACO personality inventory, the Emotion Regulation Questionnaire (ERQ), the Maslach Burnout Inventory-Student Survey (MBI-SS), and the Korean Academic Engagement Inventory (KAEI). The study employed structural equation modeling to explore the direct and mediated relationships between personality traits, emotion regulation, academic burnout, and academic engagement. Results The findings indicated that specific personality traits, notably Extraversion, directly and indirectly influence both academic burnout and engagement, with emotion regulation serving as a mediating factor. Extraversion affected engagement directly and indirectly through cognitive reappraisal. Moreover, the burnout model revealed that, besides Extraversion, Agreeableness and Openness to experience also had a direct impact on burnout, suggesting a broader range of personality traits influencing burnout compared to engagement. Conclusions The study underscores the significant role of personality traits, particularly Extraversion, in determining academic burnout and engagement, with emotion regulation often playing a mediating role. The findings of this study indicate that personality traits can be approached in a distinct manner when developing strategies to mitigate burnout and increase engagement among dental students. These insights could inform targeted interventions aimed at improving academic engagement and performance.