Objective: To establish local diagnostic reference levels (DRLs) for pediatric neck CT based on age, weight, and water-equivalent diameter (WED) across multiple university hospitals in South Korea. Materials and Methods: This retrospective study analyzed pediatric neck CT examinations from nine university hospitals, involving patients aged 0–18 years. Data were categorized by age, weight, and WED, and radiation dose metrics, including volume CT dose index (CTDIvol) and dose length product, were recorded. Data retrieval and analysis were conducted using a commercially available dose-management system (Radimetrics, Bayer Healthcare). Local DRLs were established following the International Commission on Radiological Protection guidelines, using the 75th percentile as the reference value. Results: A total of 1159 CT examinations were analyzed, including 169 scans from Institution 1, 132 from Institution 2, 126 from Institution 3, 129 from Institution 4, 128 from Institution 5, 105 from Institution 6, 162 from Institution 7, 127 from Institution 8, and 81 from Institution 9. Radiation dose metrics increased with age, weight, and WED, showing significant variability both within and across institutions. For patients weighing less than 10 kg, the DRL for CTDIvol was 5.2 mGy. In the 10–19 kg group, the DRL was 5.8 mGy; in the 20–39 kg group, 7.6 mGy; in the 40–59 kg group, 11.0 mGy; and for patients weighing 60 kg or more, 16.2 mGy. DRLs for CTDIvol by age groups were as follows: 5.3 mGy for infants under 1 year, 5.7 mGy for children aged 1–4 years, 7.6 mGy for ages 5–9 years, 11.2 mGy for ages 10–14 years, and 15.6 mGy for patients 15 years or older. Conclusion Local DRLs for pediatric neck CT were established based on age, weight, and WED across nine university hospitals in South Korea.

Objective: To establish local diagnostic reference levels (DRLs) for pediatric neck CT based on age, weight, and water-equivalent diameter (WED) across multiple university hospitals in South Korea. Materials and Methods: This retrospective study analyzed pediatric neck CT examinations from nine university hospitals, involving patients aged 0–18 years. Data were categorized by age, weight, and WED, and radiation dose metrics, including volume CT dose index (CTDIvol) and dose length product, were recorded. Data retrieval and analysis were conducted using a commercially available dose-management system (Radimetrics, Bayer Healthcare). Local DRLs were established following the International Commission on Radiological Protection guidelines, using the 75th percentile as the reference value. Results: A total of 1159 CT examinations were analyzed, including 169 scans from Institution 1, 132 from Institution 2, 126 from Institution 3, 129 from Institution 4, 128 from Institution 5, 105 from Institution 6, 162 from Institution 7, 127 from Institution 8, and 81 from Institution 9. Radiation dose metrics increased with age, weight, and WED, showing significant variability both within and across institutions. For patients weighing less than 10 kg, the DRL for CTDIvol was 5.2 mGy. In the 10–19 kg group, the DRL was 5.8 mGy; in the 20–39 kg group, 7.6 mGy; in the 40–59 kg group, 11.0 mGy; and for patients weighing 60 kg or more, 16.2 mGy. DRLs for CTDIvol by age groups were as follows: 5.3 mGy for infants under 1 year, 5.7 mGy for children aged 1–4 years, 7.6 mGy for ages 5–9 years, 11.2 mGy for ages 10–14 years, and 15.6 mGy for patients 15 years or older. Conclusion Local DRLs for pediatric neck CT were established based on age, weight, and WED across nine university hospitals in South Korea.

Synthetic data, generated using advanced artificial intelligence (AI) techniques, replicates the statistical properties of real-world datasets while excluding identifiable information.Although synthetic data does not consist of actual data points, it is derived from original datasets, thereby enabling analyses that yield results comparable to those obtained with real data. Synthetic datasets are evaluated based on their utility—a measure of how effectively they mirror real data for analytical purposes. This paper presents the generation of synthetic datasets through the Healthcare Big Data Showcase Project (2019–2023). The original dataset comprises comprehensive multi-omics data from 400 individuals, including cancer survivors, chronic disease patients, and healthy participants. Synthetic data facilitates efficient access and robust analyses, serving as a practical tool for research and education. It addresses privacy concerns, supports AI research, and provides a foundation for innovative applications across diverse fields, such as public health and precision medicine.

Objective: This study aimed to validate the reliability and validity of the Diagnostic Interview for the Internet Addiction Scale (DIA) among Korean children and adolescents in the clinical setting. Methods: We collected the clinical data from university hospitals in South Korea and 194 children and adolescents (aged 7–18 years) completed the questionnaire. The content validity was conducted on 10 items of the DIA and an internal consistency test was performed for the verification of reliability. Results: Participants on average, aged 13.17 years (standard deviation=2.46), and 75.3% (n=146) were boys. The DIA was highly correlated with the scores of the Korean scale for Internet addiction for adolescents, Young’s Internet Addiction Test, Internet addiction proneness scale for children and adolescents. The overall sampling suitability of the 10-item scale was tested using the Kaiser–Meyer–Olkin, resulting in a high value of 0.861. The DIA revealed a two-factor structure and the Cronbach’s alpha correlation coefficient for the total scale was 0.806. Confirmatory factor analysis showed an acceptable model fit (root-mean square error of approximation=0.058, comparative fit index=0.950, and Tucker-Lewis Index=0.919). Conclusion The DIA may suggest in-depth-scale examinations of the factors that influence Internet addiction. We may expect that DIA would be used efficiently for the diagnosing of Internet addiction and further studies for the assessment.

Background: We investigated whether nutritional intake is associated with physical activity (PA) and handgrip strength (HGS) in individuals with airflow limitation. Methods: This study analyzed data from the 2014 and 2016 Korean National Health and Nutrition Examination Survey. We assessed total protein intake (g/day), caloric intake (kcal/day), and other nutritional intakes, using a 24-hour dietary recall questionnaire. HGS was measured three times for each hand using a digital grip strength dynamometer, and PA was assessed as health-enhancing PA. Airflow limitation was defined as a forced expiratory volume/forced vital capacity ratio of 0.7 in individuals over 40 years of age. Participants were categorized into groups based on their PA levels and HGS measurements: active aerobic PA vs. non-active aerobic PA, and normal HGS vs. low HGS. Results: Among the 622 individuals with airflow limitation, those involved in active aerobic PA and those with higher HGS had notably higher total food, calorie, water, protein, and lipid intake. The correlations between protein and caloric intake with HGS were strong (correlation coefficients=0.344 and 0.346, respectively). The forest plots show that higher intakes of food, water, calories, protein, and lipids are positively associated with active aerobic PA, while higher intakes of these nutrients are inversely associated with low HGS. However, in the multivariate logistic regression analysis, no significant associations were observed between nutritional intake and active aerobic PA or HGS. Conclusion Nutritional intake was found to not be an independent factor associated with PA and HGS. However, the observed correlations suggest potential indirect effects that warrant further investigation.

Background and Objectives: Cigarette smoking is a major risk factor for atherosclerosis.Nicotine, a crucial constituent of tobacco, contributes to atherosclerosis development and progression. However, evidence of the association between nicotine and neointima formation is limited. We aimed to evaluate whether nicotine enhances neointimal hyperplasia in the native epicardial coronary arteries of pigs after percutaneous coronary intervention (PCI) with drug-eluting stents (DES). Methods: After coronary angiography (CAG) and quantitative coronary angiography (QCA), we implanted 20 DES into 20 pigs allocated to 2 groups: no-nicotine (n=10) and nicotine (n=10) groups. Post-PCI CAG and QCA were performed immediately. Follow-up CAG, QCA, optical coherence tomography (OCT), and histopathological analyses were performed 2 months post-PCI. Results: Despite intergroup similarities in the baseline QCA findings, OCT analysis showed that the nicotine group had a smaller mean stent and lumen areas, a larger mean neointimal area, greater percent area stenosis, and higher peri-strut fibrin and inflammation scores than the no-nicotine group. In immunofluorescence analysis, the nicotine group displayed higher expression of CD68 and α-smooth muscle actin but lower CD31 expression than the no-nicotine group. Conclusions Nicotine inhibited re-endothelialization and promoted inflammation and NIH after PCI with DES in a porcine model.

This study explored the evolving trends in pediatric dentistry research, focusing on the changes in research trends in the Journal of the Korean Academy of Pediatric Dentistry (JKAPD) and comparing them with those in other international journals and previous studies. We selected the JKAPD (Korea), Pediatric Dentistry (PD, USA), European Archives of Paediatric Dentistry (EAPD, Europe), and The Japanese Journal of Pediatric Dentistry (JJPD, Japan) as subjects for this study, as each one is considered the core academic journals of the corresponding region. Data from the four journals were collected by reviewing articles published over 20 years from 2004 to 2023. Sixteen classification criteria were established, and 4,231 papers were assigned a classification number. This study included 1,205 studies from the JKAPD, 1,320 from the PD, 1,070 from the EAPD, and 636 from the JJPD. Publication trends were similar across the pediatric dental journals; however, the JJPD showed no correlation with other journals. Dental caries and prevention of dental caries were the most published topics in all journals (15.4%), followed by systemic diseases or patients with special health care needs (9.9%), conservative treatment and restorative materials (9.2%), and dental growth and developmental disturbances (8.8%). The thematic distribution of articles in the JKAPD observed in this study is consistent with that of previous studies. Although there were regional variations, the distribution of publication trends did not significantly change before or after the 21st century. This study offers valuable insights for comparing and analyzing trends in domestic and international research and providing an opportunity to examine which social and environmental changes have influenced these trends.

This study investigated the plaque removal efficacy of a suction-type sonic toothbrush compared to a conventional manual toothbrush in preschool children aged 30 to 59 months. Using a randomized, double-blind, crossover design with a 2-week washout period, 20 pediatric participants were allocated to two study phases, each using either the suction-type sonic toothbrush or the manual toothbrush with caregiver assistance. The plaque removal effectiveness was assessed through the Silness and Löe plaque index and quantitative light-induced fluorescence values, including ΔR30 and ΔR120 indicators of plaque index. The result showed no statistically significant differences in plaque removal efficacy between the two toothbrushes, although both showed similar improvements. Caregiver feedback revealed high acceptability of the suction-type sonic toothbrush due to its convenience and engaging features, such as a light and suction function, which enhanced the tooth brushing experience. Although limited by the short follow-up period and small sample size, the findings suggest that suction-type sonic toothbrushes may offer practical benefits for young children requiring caregiver assistance.

Purpose: To confirm the clinical features of hemicentral retinal vein occlusion and identify predictors of visual outcomes. Methods: A retrospective analysis was conducted on patients diagnosed with hemicentral retinal vein occlusion between January 2018 and December 2022 and followed for more than 6 months. Patients underwent intravitreal injections as necessary for intraretinal edema. Visual acuity, central macular thickness, ellipsoid zone damage, and the location of inner retinal layer edema were assessed. Patients were categorized into groups A and group B based on the visual acuity at 6 months. Results: In total, 20 eyes were followed, with 15 eyes observed for up to 12 months. Seven patients (35.0%) had diabetes and 11 (55.0%) had hypertension. There was a correlation between poor vision at 6 months and hypertension (p = 0.033). The visual acuity of all patients improved from a logMAR of 0.96 at the initial visit to a logMAR of 0.35 at 6 months (p = 0.005). In the group with good initial visual acuity, there were no significant changes in visual acuity during the follow-up period (p = 0.444). The group with good visual acuity at 6 months had a lower degree of photoreceptor ellipsoid zone disruption compared to the group with poor initial vision, indicating a normal structure (p = 0.015). Conclusions During follow-up of patients with hemicentral retinal vein occlusion, overall visual acuity improved over time. Patients with good initial acuity maintained it. Favorable visual outcomes can be expected if the ellipsoid zone has a normal structure at the time of the first examination.

Synthetic data, generated using advanced artificial intelligence (AI) techniques, replicates the statistical properties of real-world datasets while excluding identifiable information.Although synthetic data does not consist of actual data points, it is derived from original datasets, thereby enabling analyses that yield results comparable to those obtained with real data. Synthetic datasets are evaluated based on their utility—a measure of how effectively they mirror real data for analytical purposes. This paper presents the generation of synthetic datasets through the Healthcare Big Data Showcase Project (2019–2023). The original dataset comprises comprehensive multi-omics data from 400 individuals, including cancer survivors, chronic disease patients, and healthy participants. Synthetic data facilitates efficient access and robust analyses, serving as a practical tool for research and education. It addresses privacy concerns, supports AI research, and provides a foundation for innovative applications across diverse fields, such as public health and precision medicine.