https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/456 2026-07-03T23:07:36Z https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/214350 Title: Optimal Strategy for Thromboprophylaxis in Fontan Circulation: A Systematic Review and Meta-analysis with a Focus on Ethnic Differences Authors: Oh, Kyung-Jin; Lee, Jue Seong; Seol, Jae Hee; Choi, Hee Joung; Cho, Min Jung; Choi, Miyoung; Song, Jin Young; Jung, Jo Won; Na, Jae Yoon; Kim, Jin Ah; Kim, Soo-Jin Abstract: 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. PubMed, Embase, and Cochrane Library databases were searched to identify studies reporting the thromboembolic and bleeding outcomes of patients with Fontan circulation. 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 < 0.001), and direct oral anticoagulants (DOACs) (RR, 0.22; 95% CI, 0.01–7.57; p = 0.4) were compared with no antithrombotic therapy, and only warfarin use resulted in a statistically significant reduction in thromboembolic risk, whereas the effects of aspirin and DOACs were not 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 < 0.001), and was significantly more effective than warfarin (RR, 0.57; 95% CI, 0.37–0.88; p = 0.01). Bleeding risk showed no significant between-group differences. 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. 2026-06-01T00:00:00Z https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/213851 Title: Prediction of Retinopathy of Prematurity and Treatment in Very Low Birth Weight Infants Using Machine Learning on Nationwide Non-Imaging Clinical Data Authors: Hwang, Jae Kyoon; Jung, Donggoo; Park, Hyun-Kyung; Kim, Daehyun; Do, Hyun Jeong; Oh, Seong Hee; Kim, Seung Hyun; Kim, Tae Hyun; Jin, Hyunseung Abstract: Introduction: Retinopathy of prematurity (ROP) remains a leading cause of preventable blindness in preterm infants. This study aimed to develop machine learning (ML) models using non-imaging clinical data to predict ROP, severe ROP (sROP), and treated ROP (tROP) in very low birth weight (VLBW) infants. Methods: We utilized nationwide clinical data from the Korean Neonatal Network, including 44 perinatal and neonatal variables. Two deep learning models, Multilayer Perceptron (MLP) and Neural Oblivious Decision Ensembles (NODE), optimized for tabular data, were applied. Additionally, we developed simplified models using eight key variables selected through clinical and algorithmic relevance. Results: MLP and NODE models demonstrated high predictive performance. For the full 44-variable models, the area under the receiver operating characteristic curve (AUROC) was as follows: ROP (0.853/0.855), sROP (0.888/0.890), and tROP (0.905/0.909). The reduced 8-variable models yielded comparable AUROCs: ROP (0.851/0.855), sROP (0.895/0.895), and tROP (0.910/0.909). Conclusion: The proposed ML models based on nationwide non-imaging clinical data enable early risk identification and timely intervention for ROP in VLBW infants. This cost-effective and scalable approach may help improve outcomes, especially in resource-limited settings. Retinopathy of prematurity (ROP) is an eye condition that can affect premature babies (babies born too early, before 37 weeks of pregnancy). In ROP, abnormal blood vessels grow in the retina, which can lead to vision problems or even blindness. To prevent serious outcomes, early detection and treatment are essential. However, not all hospitals have enough trained eye specialists to screen every baby at risk. For this reason, this study aimed to develop an easier way to identify babies who may need eye examinations using commonly collected medical data. To address this goal, the researchers analyzed health records of premature babies collected across South Korea. Using a method called machine learning, which allows computers to find patterns in data, they created two computer models. These models could predict which babies were more likely to develop severe forms of ROP or need treatment. Importantly, the models used only basic clinical information like birth weight, oxygen support, and medical complications, without requiring eye images. The models showed high accuracy even when using just a few key factors. By identifying risk in this way, this type of model can help hospitals recognize high-risk babies early and refer them for specialized care, even if eye doctors are not available on site. It offers a practical, low-cost tool for improving ROP screening programs, especially in areas with limited resources. 2026-06-01T00:00:00Z https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/212943 Title: Long-term effects of preterm birth on cortical folding trajectories in early childhood Authors: Jang, Yong Hun; Kim, Jong Min; Lee, Bong Gun; Hoh, Jeong-Kyu; Lee, Gang Yi; Kim, Hyun Ho; Lyu, Ilwoo; Lee, Hyun Ju Abstract: Cortical folding emerges in the late prenatal period and undergoes rapid reorganization during early childhood. However, the long-term impact of folding alterations associated with preterm birth remains unclear. Herein, we analysed the structural MRI data of 56 preterm children and 206 full-term peers aged 1–7 years. We derived cortical metrics from the reconstructed cortical surfaces using a vertex-wise computation framework to characterize regional folding patterns. We then conducted a combined analysis of the local gyrification index and sulcal depth to explain folding patterns in the preterm brain. Compared with their full-term peers, preterm children exhibited a region-specific impairment pattern characterized by a significantly reduced local gyrification index and sulcal depth in the bilateral superior temporal gyrus and left superior frontal gyrus (P < 0.05). Notably, the sulcal depth in the superior temporal cortex showed significant differences between preterm and full-term children in its association with neurodevelopmental outcomes (P < 0.05), indicating an atypical structure–function relationship in preterm children. The local gyrification index was significantly reduced in the right isthmus cingulate and posterior cingulate gyri (P < 0.05), reflecting a simplified gyral configuration. The study findings suggest several folding patterns that capture diverse mechanisms of morphogenetic disruption, indicating that preterm birth induces persistent region-specific impairments in cortical folding that may affect neurodevelopmental domains. These folding-sensitive markers provide critical insights into the development of targeted interventions to optimize long-term neurodevelopmental outcomes. 2026-05-01T00:00:00Z https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/212469 Title: Distinct early-life gut microbiota patterns across SGA, AGA, and LGA infants Authors: Hwang, Jae Kyoon; Lim, Sung Min; Kwak, Min-Jin; Kim, Seung Hyun; Kang, Yoongu; Mustafa, Ghulam; Tanpure, Rahul Sadashiv; Jeon, Byong-Hun; Hoh, Jeong-Kyu; Park, Hyun-Kyung Abstract: Birthweight-for-gestational-age influences neonatal physiology and health, yet its role in shaping early gut microbiome development remains insufficiently defined. Small-for-gestational-age (SGA), appropriate-for-gestational-age (AGA), and large-for-gestational-age (LGA) infants may exhibit distinct microbial maturation patterns that could influence later metabolic and developmental outcomes. We conducted a prospective cohort study and enrolled 50 late-preterm and term infants and classified them into SGA (n=18), AGA (n=20), and LGA (n=12). Serial fecal samples were collected at four postnatal time windows (0-14 and 15-80 days). 16S rRNA gene sequencing using Oxford Nanopore MinION characterized microbial composition, diversity, and community networks. Bioinformatic analyses included alpha- and beta-diversity metrics, co-occurrence network analysis, and functional pathway inference using PICRUSt2 mapped to the MetaCyc database. Clinical variables, including feeding pattern and antibiotic exposure, were assessed. Gut microbiome development differed according to birthweight categories. Microbial diversity increased with postnatal age, with SGA infants showing distinct community structures over time. Firmicutes predominated across all groups, while specific taxa exhibited group-specific patterns, including enrichment of Streptococcus spp. in LGA infants and Klebsiella spp. in SGA infants. Co-occurrence network analysis revealed a stable gut microbiota in LGA infants.Conclusion: Birthweight-for-gestational-age status was associated with distinct trajectories of early gut microbial maturation. SGA infants exhibited delayed microbial stabilization and fragmented interaction networks, whereas LGA infants demonstrated relatively early establishment of stable, Streptococcus-enriched communities. These growth-specific microbial patterns may reflect differences in early metabolic programming and highlight the potential importance of tailored microbiome-targeted strategies to optimize neonatal development. What is Known:center dot Abnormal fetal growth is associated with increased neonatal morbidity and long-term metabolic risk.center dot Early-life gut microbiota play an important role in immune and metabolic development.What is New:center dot This longitudinal study demonstrates growth-specific trajectories of early gut microbial maturation among SGA, AGA, and LGA infants born at >= 35-week gestation.center dot SGA infants exhibit delayed microbial stabilization and fragmented microbial interaction networks, whereas LGA infants show relatively earlier establishment of stable microbial communities. 2026-04-01T00:00:00Z