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    <title>ScholarWorks Collection:</title>
    <link>https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/456</link>
    <description />
    <pubDate>Fri, 24 Jul 2026 12:44:33 GMT</pubDate>
    <dc:date>2026-07-24T12:44:33Z</dc:date>
    <item>
      <title>Incidence and multisystem preadolescent complications of Turner syndrome: a nationwide study</title>
      <link>https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/219174</link>
      <description>Title: Incidence and multisystem preadolescent complications of Turner syndrome: a nationwide study
Authors: Cha, Jong Ho; Kang, Eungu; Na, Jae Yoon; Ryu, Soorack; Choi, Young-Jin; Kim, Ja Hye
Abstract: Background: Turner syndrome (TS) is the most common sex chromosome aneuploidy and is associated with various comorbidities. Using data from the National Health Screening Program for Infants and Children (NHSPIC), we aimed to investigate the multisystem comorbidities and growth trajectories of patients with TS in South Korea. Methods: A total of 1,647,140 female individuals born between 2007 and 2017 registered in the National Health Insurance Service were included in this study. Diagnoses of TS were based on the World Health Organization&amp;apos;s International Classification of Diseases, Tenth Revision (ICD-10). Multisystem comorbidities were categorized into cardiovascular, endocrine, neurologic, and neurosensory disorders. The risk of comorbidities was investigated using a Cox proportional-hazards regression analysis. Each individual was observed until 2020.12.31. Growth measurements from 0 to 6 years were obtained from the NHSPIC and converted into Z-scores. Growth curves of children with TS from birth to age 6 were plotted using a locally estimated scatterplot smoothing function. Results: Overall, 514 girls were diagnosed with TS. The incidence of TS was 1 per 3203 female live births over the observation period, with a median age at diagnosis of 7.6 years. Compared to the control group, the TS group had an elevated risk of various complications: congenital heart disease (CHD) (adjusted hazard ratio [aHR] 3.51; 95 % confidence interval [CI] 2.79-4.42), short stature (aHR 23.19; 95 % CI 20.99-25.61), and developmental delay (aHR 6.21; 95 % CI 4.65-8.29). Growth curves for girls with TS revealed growth impairments evident from birth. Conclusion: Our nationwide study emphasizes the importance of early diagnosis by highlighting the risk of various early TS complications. Clinicians should recognize that TS may present with early growth deficiency and a broad spectrum of multisystem comorbidities, underscoring the importance of timely diagnosis and multidisciplinary management.</description>
      <pubDate>Wed, 01 Jul 2026 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/219174</guid>
      <dc:date>2026-07-01T00:00:00Z</dc:date>
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    <item>
      <title>Optimal Strategy for Thromboprophylaxis in Fontan Circulation: A Systematic Review and Meta-analysis with a Focus on Ethnic Differences</title>
      <link>https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/214350</link>
      <description>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 &amp;lt; 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 &amp;lt; 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.</description>
      <pubDate>Mon, 01 Jun 2026 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/214350</guid>
      <dc:date>2026-06-01T00:00:00Z</dc:date>
    </item>
    <item>
      <title>Prediction of Retinopathy of Prematurity and Treatment in Very Low Birth Weight Infants Using Machine Learning on Nationwide Non-Imaging Clinical Data</title>
      <link>https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/213851</link>
      <description>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.</description>
      <pubDate>Mon, 01 Jun 2026 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/213851</guid>
      <dc:date>2026-06-01T00:00:00Z</dc:date>
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    <item>
      <title>2025 Korean Guidelines for Cardiopulmonary Resuscitation: Part 7. Pediatric basic life support</title>
      <link>https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/218436</link>
      <description>Title: 2025 Korean Guidelines for Cardiopulmonary Resuscitation: Part 7. Pediatric basic life support
Authors: Lee, Jisook; Kim, Do Kyun; Kim, Jin-Tae; Na, Jae Yoon; Park, Bobae; Jeong, Soo In; Park, June Dong; Chung, Sung Phil; Kim, Tae-Youn; Sohn, Youdong; Shim, Gyuhong; Jung, Young Hwa; Oh, Yunhee; Youn, Chun Song; Lee, Mi Jin; Lee, Chang Hee; Jang, Youngbin; Jang, Yong Soo; Cho, Gyu Chong; Cha, Kyoung-Chul; Heo, Ju Sun; Hwang, Sung Oh
Abstract: Pediatric cardiac arrest primarily arises from asphyxia in infants and trauma in older children, contrasting with adult etiologies dominated by cardiac events. This underscores prevention as the cornerstone of pediatric basic life support, through injury mitigation like child restraint systems and water supervision, safe sleep practices including supine positioning on firm surfaces with caregiver smoking cessation to reduce sudden infant death syndrome, plus awareness of child abuse and adolescent suicide prevention. In hospitals, pediatric early warning systems (PEWS) enable early deterioration detection via vital sign scoring for timely intervention. Major updates in the 2025 pediatric basic life support guidelines reflect evidence-driven refinements. First, hospitals should implement PEWS to prompt rapid response teams for at-risk inpatients. Second, all rescuers (lay and healthcare providers) should employ the two-thumb encircling hands technique for infant chest compressions for optimal depth (about 4 cm), rate (100-120/min), and recoil; one-hand heel compression serves as backup if infeasible. Third, lay rescuers may apply automated external defibrillators for nontraumatic out-of-hospital cardiac arrest in children aged 1 year or older, prioritizing prompt attachment after initial cardiopulmonary resuscitation (CPR) cycles to address potential shockable rhythms. Fourth, for infant foreign body airway obstruction, alternate five back blows (over the spine between scapulae) with five chest thrusts (using heel-of-hand on sternum) until cleared or unresponsive, then transition to CPR. These updates aim to enhance bystander intervention, CPR quality, and survival with favorable neurologic outcomes in pediatric cardiac arrest.</description>
      <pubDate>Mon, 01 Jun 2026 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/218436</guid>
      <dc:date>2026-06-01T00:00:00Z</dc:date>
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